Use of in vitro methods combined with in silico analysis to identify potential skin sensitizers in the Tox21 10K compound library.

Introduction: Skin sensitization, which leads to allergic contact dermatitis, is a key toxicological endpoint with high occupational and consumer prevalence. This study optimized several in vitro assays listed in OECD skin sensitization test guidelines for use on a quantitative high-throughput screening (qHTS) platform and performed in silico model predictions to assess the skin sensitization potential of prioritized compounds from the Tox21 10K compound library. Methods: First, we screened the entire Tox21 10K compound library using a qHTS KeratinoSensTM (KS) assay and built a quantitative structure-activity relationship (QSAR) model based on the KS results. From the qHTS KS screening results, we prioritized 288 compounds to cover a wide range of structural chemotypes and tested them in the solid phase extraction-tandem mass spectrometry (SPE-MS/MS) direct peptide reactivity assay (DPRA), IL-8 homogeneous time-resolved fluorescence (HTRF) assay, CD86 and CD54 surface expression in THP1 cells, and predicted in silico sensitization potential using the OECD QSAR Toolbox (v4.5). Results: Interpreting tiered qHTS datasets using a defined approach showed the effectiveness and efficiency of in vitro methods. We selected structural chemotypes to present this diverse chemical collection and to explore previously unidentified structural contributions to sensitization potential. Discussion: Here, we provide a skin sensitization dataset of unprecedented size, along with associated tools, and analysis designed to support chemical assessments.

Potential AhR-independent mechanisms of 2,3,7,8-Tetrachlorodibenzo-p-dioxin inhibition of human glioblastoma A172 cells migration.

The toxicity of 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is generally believed to be mediated by aryl hydrocarbon receptor (AhR), but some evidence suggests that the effects of TCDD can also be produced through AhR-independent mechanisms. In previous experiments, we found that mainly AhR-dependent mechanism was involved in the migration inhibition of glioblastoma U87 cells by TCDD. Due to the heterogeneity of glioblastomas, not all tumor cells have significant AhR expression. The effects and mechanisms of TCDD on the migration of glioblastomas with low AhR expression are still unclear. We employed a glioblastoma cell line A172 with low AhR expression as a model, using wound healing and Transwell® assay to detect the effect of TCDD on cell migration. We found that TCDD can inhibit the migration of A172 cells without activating AhR signaling pathway. Further, after being pre-treated with AhR antagonist CH223191, the inhibition of TCDD on A172 cells migration was not changed, indicating that the effect of TCDD on A172 cells is not dependent on AhR activation. By transcriptome sequencing analysis, we propose dysregulation of the expression of certain migration-related genes, such as IL6, IL1B, CXCL8, FOS, SYK, and PTGS2 involved in cytokines, MAPK, NF-κB, and IL-17 signaling pathways, as potential AhR-independent mechanisms that mediate the inhibition of TCDD migration in A172 cells.

Auranofin targets UBA1 and enhances UBA1 activity by facilitating ubiquitin trans-thioesterification to E2 ubiquitin-conjugating enzymes.

UBA1 is the primary E1 ubiquitin-activating enzyme responsible for generation of activated ubiquitin required for ubiquitination, a process that regulates stability and function of numerous proteins. Decreased or insufficient ubiquitination can cause or drive aging and many diseases. Therefore, a small-molecule enhancing UBA1 activity could have broad therapeutic potential. Here we report that auranofin, a drug approved for the treatment of rheumatoid arthritis, is a potent UBA1 activity enhancer. Auranofin binds to the UBA1's ubiquitin fold domain and conjugates to Cys1039 residue. The binding enhances UBA1 interactions with at least 20 different E2 ubiquitin-conjugating enzymes, facilitating ubiquitin charging to E2 and increasing the activities of seven representative E3s in vitro. Auranofin promotes ubiquitination and degradation of misfolded ER proteins during ER-associated degradation in cells at low nanomolar concentrations. It also facilitates outer mitochondrial membrane-associated degradation. These findings suggest that auranofin can serve as a much-needed tool for UBA1 research and therapeutic exploration.

Identification of Potent and Selective Acetylcholinesterase/Butyrylcholinesterase Inhibitors by Virtual Screening.

Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) play important roles in human neurodegenerative disorders such as Alzheimer's disease. In this study, machine learning methods were applied to develop quantitative structure-activity relationship models for the prediction of novel AChE and BChE inhibitors based on data from quantitative high-throughput screening assays. The models were used to virtually screen an in-house collection of ∼360K compounds. The optimal models achieved good performance with area under the receiver operating characteristic curve values ranging from 0.83 ± 0.03 to 0.87 ± 0.01 for the prediction of AChE/BChE inhibition activity and selectivity. Experimental validation showed that the best-performing models increased the assay hit rate by several folds. We identified 88 novel AChE and 126 novel BChE inhibitors, 25% (AChE) and 53% (BChE) of which showed potent inhibitory effects (IC50 < 5 µM). In addition, structure-activity relationship analysis of the BChE inhibitors revealed scaffolds for chemistry design and optimization. In conclusion, machine learning models were shown to efficiently identify potent and selective inhibitors against AChE and BChE and novel structural series for further design and development of potential therapeutics against neurodegenerative disorders.

Predictive Models for Human Cytochrome P450 3A7 Selective Inhibitors and Substrates.

Inappropriate use of prescription drugs is potentially more harmful in fetuses/neonates than in adults. Cytochrome P450 (CYP) 3A subfamily undergoes developmental changes in expression, such as a transition from CYP3A7 to CYP3A4 shortly after birth, which provides a potential way to distinguish medication effects on fetuses/neonates and adults. The purpose of this study was to build first-in-class predictive models for both inhibitors and substrates of CYP3A7/CYP3A4 using chemical structure analysis. Three metrics were used to evaluate model performance: area under the receiver operating characteristic curve (AUC-ROC), balanced accuracy (BA), and Matthews correlation coefficient (MCC). The performance varied for each CYP3A7/CYP3A4 inhibitor/substrate model depending on the data set type, model type, rebalancing method, and specific feature set. For the active inhibitor/substrate data set, the optimal models achieved AUC-ROC values ranging from 0.77 ± 0.01 to 0.84 ± 0.01. For the selective inhibitor/substrate data set, the optimal models achieved AUC-ROC values ranging from 0.72 ± 0.02 to 0.79 ± 0.04. The predictive power of the optimal models was validated by compounds with known potencies as CYP3A7/CYP3A4 inhibitors or substrates. In addition, we identified structural features significant for CYP3A7/CYP3A4 selective or common inhibitors and substrates. In summary, the top performing models can be further applied as a tool to rapidly evaluate the safety and efficacy of new drugs separately for fetuses/neonates and adults. The significant structural features could guide the design of new therapeutic drugs as well as aid in the optimization of existing medicine for fetuses/neonates.

Prediction of drug-induced liver injury and cardiotoxicity using chemical structure and in vitro assay data.

Drug-induced liver injury (DILI) and cardiotoxicity (DICT) are major adverse effects triggered by many clinically important drugs. To provide an alternative to in vivo toxicity testing, the U.S. Tox21 consortium has screened a collection of ∼10K compounds, including drugs in clinical use, against >70 cell-based assays in a quantitative high-throughput screening (qHTS) format. In this study, we compiled reference compound lists for DILI and DICT and compared the potential of Tox21 assay data with chemical structure information in building prediction models for human in vivo hepatotoxicity and cardiotoxicity. Models were built with four different machine learning algorithms (e.g., Random Forest, Naïve Bayes, eXtreme Gradient Boosting, and Support Vector Machine) and model performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC-ROC). Chemical structure-based models showed reasonable predictive power for DILI (best AUC-ROC = 0.75 ± 0.03) and DICT (best AUC-ROC = 0.83 ± 0.03), while Tox21 assay data alone only showed better than random performance. DILI and DICT prediction models built using a combination of assay data and chemical structure information did not have a positive impact on model performance. The suboptimal predictive performance of the assay data is likely due to insufficient coverage of an adequately predictive number of toxicity mechanisms. The Tox21 consortium is currently expanding coverage of biological response space with additional assays that probe toxicologically important targets and under-represented pathways that may improve the prediction of in vivo toxicity such as DILI and DICT.

Systematic identification of molecular mechanisms for aryl hydrocarbon receptor mediated neuroblastoma cell migration.

Tumor cell migration is affected by the aryl hydrocarbon receptor (AhR). However, the systematic molecular mechanisms underlying AhR-mediated migration of human neuroblastoma cells are not fully understood. To address this issue, we performed an integrative analysis of mRNA and microRNA (miR) expression profiles in human neuroblastoma SK-N-SH cells treated with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), a potent agonist of AhR. The cell migration was increased in a time- and concentration- dependent manner, and was blocked by AhR antagonist (CH223191). A total of 4,377 genes were differentially expressed after 24-hour-treatment with 10-10 M TCDD, of which the upregulated genes were significantly enriched in cell migration-related biological pathways. Thirty-four upregulated genes, of which 25 were targeted by 78 differentially expressed miRs, in the axon guidance pathway were experimentally confirmed, and the putative dioxin-responsive elements were present in the promoter regions of most genes (79 %) and miRs (82 %) in this pathway. Furthermore, two promigratory genes (CFL2 and NRP1) induced by TCDD was reversed by blockade of AhR. In conclusion, AhR-mediated mRNA-miR networks in the axon guidance pathway may represent a potential molecular mechanism of dioxin-induced directional migration of human neuroblastoma cells.

Repurposing drugs as COVID-19 therapies: A toxicity evaluation.

Drug repurposing is an appealing method to address the Coronavirus 2019 (COVID-19) pandemic because of the low cost and efficiency. We analyzed our in-house database of approved drug screens and compared their activity profiles with results from a severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) cytopathic effect (CPE) assay. The activity profiles of the human ether-à-go-go-related gene (hERG), phospholipidosis (PLD), and many cytotoxicity screens were found significantly correlated with anti-SARS-CoV-2 activity. hERG inhibition is a nonspecific off-target effect that has contributed to promiscuous drug interactions, whereas drug-induced PLD is an undesirable effect linked to hERG blockers. Thus, this study identifies preferred drug candidates as well as chemical structures that should be avoided because of their potential to induce toxicity. Lastly, we highlight the hERG liability of anti-SARS-CoV-2 drugs currently enrolled in clinical trials.

Efficient Identification of Anti-SARS-CoV-2 Compounds Using Chemical Structure- and Biological Activity-Based Modeling.

Identification of anti-SARS-CoV-2 compounds through traditional high-throughput screening (HTS) assays is limited by high costs and low hit rates. To address these challenges, we developed machine learning models to identify compounds acting via inhibition of the entry of SARS-CoV-2 into human host cells or the SARS-CoV-2 3-chymotrypsin-like (3CL) protease. The optimal classification models achieved good performance with area under the receiver operating characteristic curve (AUC-ROC) values of >0.78. Experimental validation showed that the best performing models increased the assay hit rate by 2.1-fold for viral entry inhibitors and 10.4-fold for 3CL protease inhibitors compared to those of the original drug repurposing screens. Twenty-two compounds showed potent (<5 µM) antiviral activities in a SARS-CoV-2 live virus assay. In conclusion, machine learning models can be developed and used as a complementary approach to HTS to expand compound screening capacities and improve the speed and efficiency of anti-SARS-CoV-2 drug discovery.

Identification of Compounds for Butyrylcholinesterase Inhibition.

Butyrylcholinesterase (BChE) is a nonspecific cholinesterase enzyme that hydrolyzes choline-based esters. BChE plays a critical role in maintaining normal cholinergic function like acetylcholinesterase (AChE) through hydrolyzing acetylcholine (ACh). Selective BChE inhibition has been regarded as a viable therapeutic approach in Alzheimer's disease. As of now, a limited number of selective BChE inhibitors are available. To identify BChE inhibitors rapidly and efficiently, we have screened 8998 compounds from several annotated libraries against an enzyme-based BChE inhibition assay in a quantitative high-throughput screening (qHTS) format. From the primary screening, we identified a group of 125 compounds that were further confirmed to inhibit BChE activity, including previously reported BChE inhibitors (e.g., bambuterol and rivastigmine) and potential novel BChE inhibitors (e.g., pancuronium bromide and NNC 756), representing diverse structural classes. These BChE inhibitors were also tested for their selectivity by comparing their IC50 values in BChE and AChE inhibition assays. The binding modes of these compounds were further studied using molecular docking analyses to identify the differences between the interactions of these BChE inhibitors within the active sites of AChE and BChE. Our qHTS approach allowed us to establish a robust and reliable process to screen large compound collections for potential BChE inhibitors.

A Universal and High-Throughput Proteomics Sample Preparation Platform.

Major advances have been made to improve the sensitivity of mass analyzers, spectral quality, and speed of data processing enabling more comprehensive proteome discovery and quantitation. While focus has recently begun shifting toward robust proteomics sample preparation efforts, a high-throughput proteomics sample preparation is still lacking. We report the development of a highly automated universal 384-well plate sample preparation platform with high reproducibility and adaptability for extraction of proteins from cells within a culture plate. Digestion efficiency was excellent in comparison to a commercial digest peptide standard with minimal sample loss while improving sample preparation throughput by 20- to 40-fold (the entire process from plated cells to clean peptides is complete in ∼300 min). Analysis of six human cell types, including two primary cell samples, identified and quantified ∼4,000 proteins for each sample in a single high-performance liquid chromatography (HPLC)-tandem mass spectrometry injection with only 100-10K cells, thus demonstrating universality of the platform. The selected protein was further quantified using a developed HPLC-multiple reaction monitoring method for HeLa digests with two heavy labeled internal standard peptides spiked in. Excellent linearity was achieved across different cell numbers indicating a potential for target protein quantitation in clinical research.

High-throughput screening assays for SARS-CoV-2 drug development: Current status and future directions.

In response to the ongoing coronavirus disease 2019 (COVID-19) pandemic, a panel of assays has been developed and applied to screen collections of approved and investigational drugs for anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) activity in a quantitative high-throughput screening (qHTS) format. In this review, we applied data-driven approaches to evaluate the ability of each assay to identify potential anti-SARS-CoV-2 leads. Multitarget assays were found to show advantages in terms of accuracy and efficiency over single-target assays, whereas target-specific assays were more suitable for investigating compound mechanisms of action. Moreover, strict filtering with counter screens might be more detrimental than beneficial in identifying true positives. Thus, developing novel HTS assays acting simultaneously against multiple targets in the SARS-CoV-2 life cycle will benefit anti-COVID-19 drug discovery.

Evaluation of chemical compounds that inhibit neurite outgrowth using GFP-labeled iPSC-derived human neurons.

Due to the increasing number of drugs and untested environmental compounds introduced into commercial use, there is recognition for a need to develop reliable and efficient screening methods to identify compounds that may adversely impact the nervous system. One process that has been implicated in neurodevelopment is neurite outgrowth; the disruption of which can result in adverse outcomes that persist later in life. Here, we developed a green fluorescent protein (GFP) labeled neurite outgrowth assay in a high-content, high-throughput format using induced pluripotent stem cell (iPSC) derived human spinal motor neurons and cortical glutamatergic neurons. The assay was optimized for use in a 1536-well plate format. Then, we used this assay to screen a set of 84 unique compounds that have previously been screened in other neurite outgrowth assays. This library consists of known developmental neurotoxicants, environmental compounds with unknown toxicity, and negative controls. Neurons were cultured for 40 h and then treated with compounds at 11 concentrations ranging from 1.56 nM to 92 µM for 24 and 48 h. Effects of compounds on neurite outgrowth were evaluated by quantifying total neurite length, number of segments, and maximum neurite length per cell. Among the 84 tested compounds, neurite outgrowth in cortical neurons and motor neurons were selectively inhibited by 36 and 31 compounds, respectively. Colchicine, rotenone, and methyl mercuric (II) chloride inhibited neurite outgrowth in both cortical and motor neurons. It is interesting to note that some compounds like parathion and bisphenol AF had inhibitory effects on neurite outgrowth specifically in the cortical neurons, while other compounds, such as 2,2',4,4'-tetrabromodiphenyl ether and caffeine, inhibited neurite outgrowth in motor neurons. The data gathered from these studies show that GFP-labeled iPSC-derived human neurons are a promising tool for identifying and prioritizing compounds with developmental neurotoxicity potential for further hazard characterization.

Systematic Identification of Molecular Targets and Pathways Related to Human Organ Level Toxicity.

The mechanisms leading to organ level toxicities are poorly understood. In this study, we applied an integrated approach to deduce the molecular targets and biological pathways involved in chemically induced toxicity for eight common human organ level toxicity end points (carcinogenicity, cardiotoxicity, developmental toxicity, hepatotoxicity, nephrotoxicity, neurotoxicity, reproductive toxicity, and skin toxicity). Integrated analysis of in vitro assay data, molecular targets and pathway annotations from the literature, and toxicity-molecular target associations derived from text mining, combined with machine learning techniques, were used to generate molecular targets for each of the organ level toxicity end points. A total of 1516 toxicity-related genes were identified and subsequently analyzed for biological pathway coverage, resulting in 206 significant pathways (p-value <0.05), ranging from 3 (e.g., developmental toxicity) to 101 (e.g., skin toxicity) for each toxicity end point. This study presents a systematic and comprehensive analysis of molecular targets and pathways related to various in vivo toxicity end points. These molecular targets and pathways could aid in understanding the biological mechanisms of toxicity and serve as a guide for the design of suitable in vitro assays for more efficient toxicity testing. In addition, these results are complementary to the existing adverse outcome pathway (AOP) framework and can be used to aid in the development of novel AOPs. Our results provide abundant testable hypotheses for further experimental validation.

New perspective on the regulation of acetylcholinesterase via the aryl hydrocarbon receptor.

Acetylcholinesterase (AChE, EC 3.1.1.7) plays important roles in cholinergic neurotransmission and has been widely recognized as a biomarker for monitoring pollution by organophosphate (OP) and carbamate pesticides. Dioxin is an emerging environmental AChE disruptor and is a typical persistent organic pollutant with multiple toxic effects on the nervous system. Growing evidence has shown that there is a significant link between dioxin exposure and neurodegenerative diseases and neurodevelopmental disorders, most of which involve AChE and cholinergic dysfunctions. Therefore, an in-depth understanding of the effects of dioxin on AChE and the related mechanisms of action might help to shed light on the molecular bases of dioxin impacts on the nervous system. In the past decade, the effects of dioxins on AChE have been revealed in cultured cells of different origins and in rodent animal models. Unlike OP and carbamate pesticides, dioxin-induced AChE disturbance is not due to direct inhibition of enzymatic activity; instead, dioxin causes alterations of AChE expression in certain models. As a widely accepted mechanism for most dioxin effects, the aryl hydrocarbon receptor (AhR)-dependent pathway has become a research focus in studies on the mechanism of action of dioxin-induced AChE dysregulation. In this mini-review, the effects of dioxin on AChE and the diverse roles of the AhR pathway in AChE regulation are summarized. Additionally, the involvement of AhR in AChE regulation during different neurodevelopmental processes is discussed. These AhR-related findings might also provide new insight into AChE regulation triggered by diverse xenobiotics capable of interacting with AhR.

Predictive Models for Human Organ Toxicity Based on In Vitro Bioactivity Data and Chemical Structure.

Traditional toxicity testing reliant on animal models is costly and low throughput, posing a significant challenge with the increasing numbers of chemicals that humans are exposed to in the environment. The purpose of this investigation was to build optimal prediction models for various human in vivo/organ-level toxicity end points (extracted from ChemIDPlus) using chemical structure and Tox21 in vitro quantitative high-throughput screening (qHTS) bioactivity assay data. Several supervised machine learning algorithms were applied to model 14 human toxicity end points pertaining to vascular, kidney, ureter and bladder, and liver organ systems. Three metrics were used to evaluate model performance: area under the receiver operating characteristic curve (AUC-ROC), balanced accuracy (BA), and Matthews correlation coefficient (MCC). The top four models, with AUC-ROC values >0.8, were derived for endocrine (0.90 ± 0.00), musculoskeletal (0.88 ± 0.02), peripheral nerve and sensation (0.85 ± 0.01), and brain and coverings (0.83 ± 0.02) toxicities, whereas the best model AUC-ROC values were >0.7 for the remaining 10 toxicities. Model performance was found to be dependent on the specific data set, model type, and feature selection method used. In addition, chemical structure and assay data showed different levels of contribution to the prediction of different toxicity end points. Although in vitro assay data, when combined with chemical structure, slightly improved the predictive accuracy for most end points (11 out of 14), a noteworthy finding was the near equal success of the structure-only models, which do not require Tox21 qHTS screening data, and the relatively poor performance of assay-only models. Thus, the top-performing structure-only models from this study could be applied for hazard screening of large sets of chemicals for potential human toxicity, whereas the largest assay contributions to models (i.e., cellular targets) could be used, along with the top-contributing structural features, to provide insight into toxicity mechanisms.

Effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin on spontaneous movement of human neuroblastoma cells.

Aryl hydrocarbon receptor (AhR) plays important roles in the interferences of dioxin exposure with the occurrence and development of tumors. Neuroblastoma is a kind of malignant tumor with high mortality and its occurrence is getting higher in dioxin exposed populations. However, there is still a lack of direct evidence of influences of dioxin on neuroblastoma cell migration. SK-N-SH is a human neuroblastoma cell line which has been used to reveal 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-induced dysregulation of certain promigratory gene. Thus, in this study, we employed SK-N-SH cells to investigate the effects of TCDD on the spontaneous movement of neuroblastoma cells, which is a short-range cell migratory behavior related to clone formation and tumor metastasis in vitro. Using unlabeled live cell imaging and high content analysis, we characterized the spontaneous movement under a full-nutrient condition in SK-N-SH cells. We found that the spontaneous movement of SK-N-SH cells was inhibited after 36- or 48-h treatment with TCDD at relative low concentrations (10-10 or 2 × 10-10 M). The TCDD-treated cells were unable to move as freely as that of control cells, resulting in less diffusive trajectories and a decreased displacement of the movement. In line with this cellular effect, the expression of pro-adhesive genes was significantly induced in time- and concentration-dependent manners after TCDD treatment. In addition, with the presence of AhR antagonist, CH223191, the effects of TCDD on the gene expression and the spontaneous cell movement were effectively reversed. Thus, we proposed that AhR-mediated up-regulation of pro-adhesive genes might be involved in the inhibitory effects of dioxin on the spontaneous movement of neuroblastoma cells. To our knowledge, this is the first piece of direct evidence about the influence of dioxin on neuroblastoma cell motility.

2,3,7,8-Tetrachlorodibenzo-p-dioxin and up-regulation of neurofilament expression in neuronal cells: Evaluation of AhR and MAPK pathways.

Dioxin exposure is reported to affect nervous system development and increase the risk of neurodegenerative diseases. Generally, dioxin exerts its neurotoxicity via aryl hydrocarbon receptor (AhR). Neurofilament (NF) light (NFL) protein is a biomarker for both neuronal differentiation and neurodegeneration and its expression is controlled by the mitogen-activated protein kinase (MAPK) pathway. However, the effects of dioxin on NFL expression and involved mechanisms are incompletely understood. We aimed to investigate the effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) on NFL expression and elucidate the underlining signaling pathways and their potential crosstalk, specifically between MAPK and AhR pathway. We employed primary cultured rat cortical neurons to evaluate the effect of TCDD exposure on NFL expression. We also used nerve growth factor (NGF)-treated PC12 cells with specific inhibitors to investigate the involvement of and potential crosstalk between the MAPK pathway and the AhR pathway in mediating the effects of TCDD on NFL expression. After TCDD exposure, NFL mRNA and protein levels were upregulated in cultured neurons. NFL protein was preferentially found in the cell body compared with neurites of the cultured neurons. In PC12 cells, TCDD enhanced both NGF-induced NFL expression and phosphorylation of ERK1/2 and p38. The addition of MAPK-pathway inhibitors (PD98059 and SB230580) partially blocked the TCDD-induced NFL upregulation. CH223191, an AhR antagonist, reversed the upregulation of NFL and phosphorylation of ERK1/2 and p38 induced by TCDD. This study demonstrated TCDD-induced upregulation of NFL in cultured neurons, with protein retained in the cell body. TCDD action was dependent on activation of AhR and MAPK, while crosstalk was found between these two signaling pathways.

2,3,7,8-Tetrachloodibenzo-p-dioxin affects the differentiation of CD4 helper T cell.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), the most toxic congener of dioxins, is a persistent and ubiquitous environmental contaminant. Although the immunotoxic effects of TCDD have been reported, the mechanisms underlying these effects are still unclear. In this study, we have determined the toxic effects of TCDD on thymocytes and splenic T cells with in vitro cell culture systems. Magnetically isolated mouse splenic Th cells, Treg cells and the mixed spleen lymphocytes (SLC) were cultured and treated with TCDD and the differentiation of CD4 Th cells was determined by flow cytometery. Our results showed that different concentrations of TCDD caused immunotoxic effects through different toxicological mechanisms in both the purified mouse splenic Th cells and the mixed SLC. The low dose exposure to TCDD triggered regulatory effects in the immune system, while the high dose TCDD exposure resulted in severe immune toxicity. Notably, a decline of Treg subset was observed, suggesting an imbalanced immune regulation by TCDD treatment, as well as a possible decrease of TCDD's indirect effects on bystander immune cells. Our CD4 Th subset co-culture experiments showed that TCDD-induced pathobiology depended on immune cell balance, suggesting that cytokine-induced microenvironments further modulated toxic effects associated with TCDD exposure.

Metabolic profiling study on potential toxicity in male mice treated with Dechlorane 602 using UHPLC-ESI-IT-TOF-MS.

Dechlorane 602 (Dec 602), a chlorinated flame retardant, has been widely detected in different environmental matrices and biota. However, toxicity data for Dec 602 seldom have been reported. A metabolomics study based on ultra-high performance liquid chromatography coupled with ion trap time-of-flight mass spectrometry was employed to study the urine and sera metabolic profiles of mice administered with Dec 602 (0, 0.001, 0.1, and 10 mg/kg body weight per day) for 7 days. A significant difference in metabolic profiling was observed between the Dec 602 treated group and the control group by multivariate analysis, which directly reflected the metabolic perturbations caused by Dec 602. The metabolomics analyses of urine from Dec 602-exposed animals exhibited an increase in the levels of thymidine and tryptophan as well as a decrease in the levels of tyrosine, 12,13-dihydroxy-9Z-octadecenoic acid, 2-hydroxyhexadecanoic acid and cuminaldehyde. The metabolomics analyses of sera showed a decrease in the levels of kynurenic acid, daidzein, adenosine, xanthurenic acid and hypoxanthine from Dec 602-exposed animals. These findings indicated Dec 602 induced disturbance in phenylalanine, tyrosine and tryptophan biosynthesis, tryptophan metabolism, tyrosine metabolism, pyrimidine metabolism, purine metabolism, ubiquinone and other terpenoid-quinone biosynthesis; phenylalanine metabolism and aminoacyl-tRNA biosynthesis. Significant alterations of immune and neurotransmitter-related metabolites (tyrosine, tryptophan, kynurenic acid, and xanthurenic acid) suggest that the toxic effects of Dec 602 may contribute to its interactions with the immune and neuronal systems. This study demonstrated that the UHPLC-ESI-IT-TOF-MS-based metabolomic approach can obtain more specific insights into the potential toxic effects of Dec 602 at molecular level.