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.

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.

Background:Although the chlorinated flame retardant Dechlorane (Dec) 602 has been detected in food, human blood, and breast milk, there is limited information on potential health effects, including possible immunotoxicity.Objectives:We determined the immunotoxic potential of Dec 602 in mice by examining the expression of phenotypic markers on thymocyte and splenic lymphocyte subsets, Th1/Th2 transcription factors, and the production of cytokines and antibodies.Methods:Adult male C57BL/6 mice were orally exposed to environmentally relevant doses of Dec 602 (1 and 10 μg/kg body weight per day) for 7 consecutive days. Thymocyte and splenic CD4 and CD8 subsets and splenocyte apoptosis were examined by flow cytometric analysis. Cytokine expression was measured at both the mRNA and the protein levels. Levels of the transcription factors Th1 (T-bet and STAT1) and Th2 (GATA3) were determined using quantitative real-time polymerase chain reaction (qPCR). Serum levels of immunoglobulins IgG1, IgG2a, IgG2b and IgE were measured by enzyme-linked immunosorbent assay (ELISA).Results:Splenic CD4+ and CD8+ T cell subsets were decreased compared with vehicle controls, and apoptosis was significantly increased in splenic CD4+ T cells. Expression (mRNA and protein) of Th2 cytokines [interleukin (IL)-4, IL-10, and IL-13] increased, and that of Th1 cytokines [IL-2, interferon (IFN)-γ and tumor necrosis factor (TNF)-α] decreased. The Th2 transcriptional factor GATA3 increased, whereas the Th1 transcriptional factors T-bet and STAT1 decreased. As additional indicators of the Th2-Th1 imbalance, production of IgG1 was significantly increased, whereas IgG2a was reduced.Conclusions:To our knowledge, we are the first to report evidence of the effects of Dec 602 on immune function in mice, with findings indicating that Dec 602 exposure favored Th2 responses and reduced Th1 function.Citation:Feng Y, Tian J, Xie HQ, She J, Xu SL, Xu T, Tian W, Fu H, Li S, Tao W, Wang L, Chen Y, Zhang S, Zhang W, Guo TL, Zhao B. 2016. Effects of acute low-dose exposure to the chlorinated flame retardant dechlorane 602 and Th1 and Th2 immune responses in adult male mice. Environ Health Perspect 124:1406–1413; http://dx.doi.org/10.1289/ehp.1510314

In response to the ongoing coronavirus disease 2019 (COVID-19) pandemic, a panel of assays have 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.

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.

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.

Since solar light energy is the source of all renewable biological energy, the direct usage of light energy by bacterial cell factory has been a very attractive concept, especially using light energy to promote anaerobic fermentation growth and even recycle low-energy carbon source when energy is the limiting factor. Proteorhodopsin(PR), a light-driven proton pump proven to couple with ATP synthesis when expressed heterogeneously, is an interesting and simple option to enable light usage in engineered strains. However, although it was reported to influence fermentation in some cases, heterogeneous proteorhodopsin expression was never shown to support growth advantage or cause metabolic shift by photophosphorylation so far. Hereby, we presented the first experimental evidence that heterogeneously expressed proteorhodopsin can provide growth advantage and cause ATP-dependent metabolism shift of acetate and lactate changes in Escherichia coli at anaerobic condition. Those discoveries suggest further application potential of PR in anaerobic fermentation where energy is a limiting factor.

Emerging evidence has shown that dioxin causes dysregulation of microRNAs (miRs) in a variety of tissues or cells. However, little is known about dioxin effects on neuronal miRs expression. In the present study, 277 differentially expressed miRs were identified by miRs microarray analysis in 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, at 10−10 M) treated SK-N-SH neuroblastoma cells. Among them, 53 miRs exhibited changes of more than 0.4-fold. Consistent with the microarray data, we verified the induction effect of TCDD on hsa-miR-608 expression, which is a primate-specific miR associated with brain functions. Bioinformatics analysis showed involvement of hsa-miR-608 in cytoskeleton organization, in which one of the hsa-miR-608 target genes, Cell Division Cycle 42 (CDC42), might play a role. We also confirmed induction of CDC42 expression by TCDD in SK-N-SH cells. TCDD induced the expression of CDC42 mRNA in hsa-miR-608 inhibitor transfected cells more obviously than in control cells, suggesting involvement of both transcriptional and post-transcriptional mechanisms in the TCDD-induced CDC42 regulation. Furthermore, CH223191, an antagonist of the aryl hydrocarbon receptor (AhR), counteracted TCDD-induced hsa-miR-608 and CDC42 expression. These results indicated that AhR not only mediates transcriptional induction of CDC42, but also hsa-miR-608-induced post-transcriptional regulation of CDC42 in dioxin treated neuroblastoma cells.