Chemical Research in Toxicology最新文献

Polyfluoroalkyl substances (PFAS) are widely used industrial compounds that have been identified as contaminants in almost every component of the global ecosystem, and in human studies, higher levels of PFAS have been correlated with increased incidence of multiple diseases. Based on the results of human and laboratory animal studies, we hypothesize that the orphan nuclear receptor 4A1 (NR4A1) may be a critical target for some PFAS such as the legacy linear polyfluorooctanesulfonate (PFOS) and other sulfonates. We show that PFOS and related compounds bound the ligand binding domain (LBD) of NR4A1 and induced the growth of several cancer cell lines and enhanced tumor growth in an athymic nude mouse model. Using NR4A1-responsive rhabdomyosarcoma Rh30 cells as a model, PFOS induced NR4A1-dependent cell proliferation and Rh30 cell migration and invasion. Moreover, in Rh30 cells, PFOS also induces several NR4A1-regulated genes including the PAX3-FOXO1 oncogene and downstream gene products, and in a chromatin immunoprecipitation assay, PFOS does not decrease NR4A1 binding to the promoter. These results demonstrate that PFOS is an NR4A1 ligand and enhances tumorigenesis through the activation of this receptor.

Urinary mercapturic acids represent valuable biological markers of chemical exposure and detoxification mechanisms. Characterization of this class of compound has historically employed LC-MS/MS analytical platforms using negative ion mode. In this study, we report the first application of a UHPLC-MS/MS method using positive ion mode detection for the unbiased characterization of mercapturic acids. A preliminary spectral library of synthetically available mercapturic acids was generated to evaluate fragmentation pathways of mercapturic acids in positive mode. From our findings, we propose a discovery method that utilizes a neutral loss monitoring paradigm based on two diagnostic fragmentation pathways of mercapturic acids. Using a cohort of 20 nonsmokers and 20 smokers, we detected 180 putative mercapturic acid signatures that exhibited a high degree of reproducibility. Following a combination of multivariate and univariate statistics, we found 33 putative mercapturic acids associated with smoking status. The increased structural insights of analytical profiling in positive mode enable more informative annotation of discovery results. Using the latest structural prediction technology, we were able to assign preliminary structural identifications to these features and eliminate likely false positive detections. From our workflow, we discovered a previously unreported mercapturic acid with a strong association with tobacco cigarette usage and putatively identified it as N-acetyl-S-(2-ethyl-3-pyridine)-l-cysteine, a potential metabolite of nicotine pyrolysis product 3-ethenylpyridine.

Drug-induced liver injury (DILI) is a major cause of drug development failures and postmarket drug withdrawals, posing significant challenges to public health and pharmaceutical research. The biological mechanisms leading to DILI are highly complex and the adverse reaction is often difficult to foresee. Hence, mechanistic insights into DILI, as well as machine learning models to predict molecular events that trigger adverse outcomes, pharmacokinetics and pharmacodynamics in the liver, are essential tools for understanding and preventing DILI. In this study, we collected a comprehensive data set of 28 in vitro endpoints related to liver toxicity and function, as well as data specific to DILI, to explore the potential of multi-task learning for their prediction. We demonstrate the benefits of ensemble modeling and provide an uncertainty estimation based on the standard deviation of the predictions to define an applicability domain for the models. Available assays at Bayer for two of the endpoints (Bile salt export pump (BSEP) inhibition and phospholipidosis) were run on a set of public compounds and used for further evaluation (data provided in the Supporting Information). Additionally, we conducted an in-depth data analysis of the relationships among the different endpoints, as well as with DILI. The presented models can be used to derive a "Virtual Liver Safety Profile" showcasing the predicted activity of a compound on the selected endpoints to support the prioritization of assays and the elucidation of modes of action.

Little cigars are similar to cigarettes, with respect to dimensions, filters, and overall appearance. Some smokers also use little cigars as substitutes for cigarettes. Comparison of little cigars with cigarettes is relevant to understanding their respective public health impact. To understand their relative toxicities, mainstream smoke yields of benzo[a]pyrene (B[a]P), a human carcinogen, were measured for 60 commercial little cigars. The little cigars were smoked on a linear smoking machine using the International Organization of Standardization (ISO) nonintense and Canadian Intense (CI) smoking regimens followed by analysis with a validated gas chromatography/mass spectrometry (GC/MS) method. The average analytical quantitative variability of the measured little cigar constituents was lower compared to previously tested commercial cigarettes (%RSD 9.6 vs 14.5, respectively). B[a]P yields ranged from 14.5-44.0 ng/cigar (ISO) and 24.0-65.7 ng/cigar (CI). The mean ISO yield is 25.5 ng/cigar versus the CI yield of 42.2 ng/cigar, which are 2.5- and 2-fold greater, respectively, than the corresponding mean cigarette yields. When normalized to tobacco weight, B[a]P yields of the little cigars are 1.5- (ISO) and 1.3- (CI) fold greater than cigarette yields. B[a]P smoke yields are known to correlate with tobacco weight. The little cigar B[a]P yield correlations to tobacco weight (CI R² = 0.35; ISO R² = 0.24) are similar to cigarette yield correlations (CI R² = 0.31; ISO R² = 0.21). Other physical properties (i.e., filter length, filter ventilation, and packing density) that may impact B[a]P smoke yields for the little cigars had very weak correlations. Except for cigarette packing density, cigars and cigarettes have similar correlations between B[a]P yields and physical design parameters. In summary, the little cigars, although physically similar to cigarettes, differ in smoke chemistry by generating higher B[a]P yields, even when normalized to tobacco weight.

Organophosphorus (OP) compounds pose a serious risk to human health by covalently modifying acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). Currently approved oxime therapeutics can reactivate OP-inhibited AChE and BChE, despite significant limitations. The OP-inhibited enzymes undergo a secondary O-dealkylation event, known as aging, for which no currently approved therapeutics are effective as treatments. Many decades of research have studied the aging mechanism in AChE and BChE. It has previously been accepted that aging occurs via a spontaneous O-dealkylation event, by loss of a carbocation or by water hydrolysis of the OP-adducted serine residue. Here, we present a novel mechanism of aging in which the catalytic histidine acts as a nucleophile to induce aging and, as a result, becomes alkylated after exposure to methyl paraoxon (MP) and other pesticides. Using bottom-up proteomics, we identify that upon aging of MP-inhibited AChE and BChE, a methyl transfer occurs from the phosphylated serine residue to the catalytic histidine residue. The extent of histidine methylation is pH-dependent as less methylation is observed at lower pH, while increased methylation is observed at higher pH. At near physiological pH (7.5), the ratio of N-MeHis/His is 3:1 for AChE and 1.3:1 for BChE after 24 h. When other OP compounds were also tested for histidine modification, ethyl paraoxon was shown to result in ethylation of the catalytic histidine; however, when the alkoxy group was branched in the case of an isopropoxy group present in diisopropyl fluorophosphate, no alkylation of histidine was observed. Recent advances in the development of quinone methide precursors show promise in the recovery of OP-aged AChE. In this work, we discuss the importance of this novel aging mechanism and its impact on the recoverability of OP-aged AChE or BChE as it appears that the histidine modification limits the overall recovery of active AChE.

High-throughput cell-based bioassays can fulfill the growing need to assess the hazards and modes of toxic action (MOA) of ionic liquids (ILs). Although nominal concentrations (C_nom) are typically used in an in vitro bioassay, freely dissolved concentrations (C_free) are considered a more accurate dose metric because they account for chemical partitioning processes and are informative about MOA. We determined the C_free of IL cations in AREc32 and AhR-CALUX assays using both mass balance model (MBM) prediction and experimental quantification. Partition coefficients between membrane lipid–water (K_mw), serum albumin–water (K_albumin/w), and cell-water (K_cell/w) as well as potential confounding factors (binding to a test plate and micelle formation) were determined to improve the MBM prediction. IL cations showed a higher affinity for both cell lines than that predicted by the MBM based on K_mw and K_albumin/w. Their affinity for the AhR-CALUX cells was more than 1 order of magnitude higher than for the AREc32, signifying cell line-specific affinity. The MBM with an experimental K_cell/w accurately predicted C_free. Evaluating cytotoxicity based on C_free eliminated the leveling off of toxicity observed for hydrophobic IL cations (side chain cutoff), suggesting that C_nom underestimates the effects of compounds with high affinity for the assay medium. Cell membrane concentrations calculated from C_free using K_mw were compared to the critical membrane burden to identify whether IL cations act as baseline toxicants. The IL cations carrying 16 carbons in the chain in the AREc32 assay and most of the IL cations in the AhR-CALUX assay were classified as excess toxicants. However, since the reasons for the deviation of experimental K_cell/w from MBM prediction remain unexplained, it is uncertain whether the cell membrane concentrations can be well predicted from K_mw used in this study. Therefore, future studies should aim to uncover the underlying causes of differing cell affinities observed across cell lines and model predictions.

Isopropyl glycidyl ether (IPGE) is a member of the large glycidyl ether family frequently used as a reactive diluent during the epoxy resin manufacturing process. Although the toxicity induced by this type of chemical has been investigated in many studies of different aspects (acute, subchronic, genotoxic, reproduction, etc.), there is still little known about their toxicokinetics. To gain information about the attainable systemic concentration, a liquid chromatography─tandem mass spectrometry (LC–MS/MS) method was developed and validated for the quantification of IPGE in rat plasma using its structural analogue tert-butyl glycidyl ether as the internal standard. Two types of atmospheric pressure ionization techniques have been utilized; however, the protonated molecule ion could not be observed in either ionization mode. First, the ammonium adduct form was used for fragmentation, albeit this multiple-reaction monitoring transition proved to be not sensitive enough for real study sample analysis. In order to achieve the desired sensitivity, the Meerwein reaction was applied as an in-source derivatization tool to generate a product by using the ethylnitrilium ion formed from the eluent acetonitrile. This gas-phase reaction enabled us to build up a method with a substantial sensitivity increase (LLOQ of 0.01 μg/mL) compared to that obtained with the ammonium adduct. After method validation, real study samples from a single-dose oral toxicity study were analyzed to evaluate the blood plasma concentration of IPGE at three dose levels. Dose-dependent superproportional systemic exposure was observed in the studied dose range (1000–2000 mg/kg). Additionally, seven metabolites of IPGE were tentatively identified in rat plasma: 3-isopropoxy-2-hydroxy-1-propanol (M1), sulfate-conjugate of IPGE (M3), glucuronide-conjugate of IPGE (M4), 3-isopropoxy-2-hydroxypropionic acid (M5), O-isopropyl-N-acetylserine (M6), O-(2-hydroxy-isopropyl)-N-acetylserine (M7), and glutathione-conjugate of IPGE (M11). Present work may pave the way to other methods that are able to quantify compounds similar to IPGE even in human plasma, which could provide valuable information to assist exposure assessment and biomonitoring in occupational health and safety studies.

Since their discovery as impurities in numerous pharmaceuticals beginning in 2018, there has been a strong push to predict and prevent the formation of mutagenic nitrosamines. Several experimental methods, particularly the Nitrosation Assay Procedure, have been developed to predict a molecule’s susceptibility to nitrosation. Here, we have compiled the results of hundreds of these experiments from the literature to construct two structure–activity relationship models: a statistical model and an expert rule-based model. The statistical model has been built with graph neural networks and was trained on a dataset of 207 nitrogen-containing molecules. This model makes a binary call for each nitrogen center, predicting if it is likely to be nitrosated or not. Conversely, the rule-based model labels each possible nitrosamine product as one of four categories, ranging from “unlikely” to “very likely”. It makes this determination based on 15 rules, which cover 12 deactivating (inhibit nitrosation) and 3 activating (favor nitrosation) features that have been drawn from the literature. Both models perform remarkably well, with accuracies of ∼80%. The rule-based model is generally biased toward favoring nitrosation while the statistical model is more likely to classify an amine as un-nitrosatable due to the makeup of the dataset. Using the models together can balance these biases and further improve the reliability of both.

The ErbB2 signaling pathway plays a crucial role in cancer stem cells (CSCs), governing cancer aggressiveness and proliferation. Targeting ErbB2 holds promise for advancing cancer therapeutics. Resveratrol (RES) and its derivatives have been noted for their ability to target proteins that are involved in CSCs. In this investigation, we synthesize novel derivatives of RES, aim at elucidating structure–activity relationships (SARs) that could enhance the anticancer properties of the RES analogues, and explore their capacities to suppress CSCs. YI-12, an O-benzyl-substituted 1,3-diphenylpropane, demonstrated the most potent anticancer activity against lung cancer cells (A549 and H460), showing high potential inhibiting cancer colony formation. Interestingly, not only does YI-12 suppress CSCs-related proteins, indicated by decreased expression of CSC-enhancing molecules such as CD133-, OCT4-, and CSC-related protein β-catenin, but it also induces apoptosis in CSC-rich spheroids after treatment. Additionally, molecular docking and bioinformatic analysis suggest ErbB2 as a potential target of the compound with a strong binding affinity (−6.709 kcal/mol) compared to the reference compound TAK-285 (−5.563 kcal/mol). YI-12’s capability to bind and inhibit ErbB2 leads to the suppression of PI3K and AKT. In conclusion, we highlight the novel resveratrol derivative YI-12 for its ability to inhibit CSCs through the ErbB2 signaling pathway. This compound represents a promising structure that should be further developed for potential use in anticancer therapy.