Progress in toxicogenomics to protect human health.

Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.

Transcriptomic analysis of AHR wildtype and Knock-out rat livers supports TCDD's role in AHR/ARNT-mediated circadian disruption and hepatotoxicity.

Single, high doses of TCDD in rats are known to cause wasting, a progressive loss of 30 to 50% body weight and death within several weeks. To identify pathway perturbations at or near doses causing wasting, we examined differentially gene expression (DGE) and pathway enrichment in centrilobular (CL) and periportal (PP) regions of female rat livers following 6 dose levels of TCDD - 0, 3, 22, 100, 300, and 1000 ng/kg/day, 5 days/week for 4 weeks. At the higher doses, rats lost weight, had increased liver/body weight ratios and nearly complete cessation of liver cell proliferation, signs consistent with wasting. DGE curves were left shifted for the CL versus the PP regions. Canonical Phase I and Phase II genes were maximally increased at lower doses and remained elevated at all doses. At lower doses, ≤ 22 ng/kg/day in the CL and ≤ 100 ng/kg/day, upregulated genes showed transcription factor (TF) enrichment for AHR and ARNT. At the mid- and high-dose doses, there was a large number of downregulated genes and pathway enrichment for DEGs which showed downregulation of many cellular metabolism processes including those for steroids, fatty acid metabolism, pyruvate metabolism and citric acid cycle. There was significant TF enrichment of the hi-dose downregulated genes for RXR, ESR1, LXR, PPARalpha. At the highest dose, there was also pathway enrichment with upregulated genes for extracellular matrix organization, collagen formation, hemostasis and innate immune system. TCDD demonstrates most of its effects through binding the aryl hydrocarbon receptor (AHR) while the downregulation of metabolism genes at higher TCDD doses is known to be independent of AHR binding to DREs. Based on our results with DEG, we provide a hypothesis for wasting in which high doses of TCDD shift circadian processes away from the resting state, leading to greatly reduced synthesis of steroids and complex lipids needed for cell growth, and producing gene expression signals consistent with an epithelial-to-mesenchymal transition in hepatocytes.

High-Throughput Transcriptomics Screen of ToxCast Chemicals in U-2 OS Cells.

New approach methodologies (NAMs) aim to accelerate the pace of chemical risk assessment while simultaneously reducing cost and dependency on animal studies. High Throughput Transcriptomics (HTTr) is an emerging NAM in the field of chemical hazard evaluation for establishing in vitro points-of-departure and providing mechanistic insight. In the current study, 1201 test chemicals were screened for bioactivity at eight concentrations using a 24-h exposure duration in the human- derived U-2 OS osteosarcoma cell line with HTTr. Assay reproducibility was assessed using three reference chemicals that were screened on every assay plate. The resulting transcriptomics data were analyzed by aggregating signal from genes into signature scores using gene set enrichment analysis, followed by concentration-response modeling of signatures scores. Signature scores were used to predict putative mechanisms of action, and to identify biological pathway altering concentrations (BPACs). BPACs were consistent across replicates for each reference chemical, with replicate BPAC standard deviations as low as 5.6 × 10-3 µM, demonstrating the internal reproducibility of HTTr-derived potency estimates. BPACs of test chemicals showed modest agreement (R2 = 0.55) with existing phenotype altering concentrations from high throughput phenotypic profiling using Cell Painting of the same chemicals in the same cell line. Altogether, this HTTr based chemical screen contributes to an accumulating pool of publicly available transcriptomic data relevant for chemical hazard evaluation and reinforces the utility of cell based molecular profiling methods in estimating chemical potency and predicting mechanism of action across a diverse set of chemicals.

High-Throughput Transcriptomics of Water Extracts Detects Reductions in Biological Activity with Water Treatment Processes.

The presence of numerous chemical contaminants from industrial, agricultural, and pharmaceutical sources in water supplies poses a potential risk to human and ecological health. Current chemical analyses suffer from limitations, including chemical coverage and high cost, and broad-coverage in vitro assays such as transcriptomics may further improve water quality monitoring by assessing a large range of possible effects. Here, we used high-throughput transcriptomics to assess the activity induced by field-derived water extracts in MCF7 breast carcinoma cells. Wastewater and surface water extracts induced the largest changes in expression among cell proliferation-related genes and neurological, estrogenic, and antibiotic pathways, whereas drinking and reclaimed water extracts that underwent advanced treatment showed substantially reduced bioactivity on both gene and pathway levels. Importantly, reclaimed water extracts induced fewer changes in gene expression than laboratory blanks, which reinforces previous conclusions based on targeted assays and improves confidence in bioassay-based monitoring of water quality.

Application of Cell Painting for chemical hazard evaluation in support of screening-level chemical assessments.

'Cell Painting' is an imaging-based high-throughput phenotypic profiling (HTPP) method in which cultured cells are fluorescently labeled to visualize subcellular structures (i.e., nucleus, nucleoli, endoplasmic reticulum, cytoskeleton, Golgi apparatus / plasma membrane and mitochondria) and to quantify morphological changes in response to chemicals or other perturbagens. HTPP is a high-throughput and cost-effective bioactivity screening method that detects effects associated with many different molecular mechanisms in an untargeted manner, enabling rapid in vitro hazard assessment for thousands of chemicals. Here, 1201 chemicals from the ToxCast library were screened in concentration-response up to ∼100 µM in human U-2 OS cells using HTPP. A phenotype altering concentration (PAC) was estimated for chemicals active in the tested range. PACs tended to be higher than lower bound potency values estimated from a broad collection of targeted high-throughput assays, but lower than the threshold for cytotoxicity. In vitro to in vivo extrapolation (IVIVE) was used to estimate administered equivalent doses (AEDs) based on PACs for comparison to human exposure predictions. AEDs for 18/412 chemicals overlapped with predicted human exposures. Phenotypic profile information was also leveraged to identify putative mechanisms of action and group chemicals. Of 58 known nuclear receptor modulators, only glucocorticoids and retinoids produced characteristic profiles; and both receptor types are expressed in U-2 OS cells. Thirteen chemicals with profile similarity to glucocorticoids were tested in a secondary screen and one chemical, pyrene, was confirmed by an orthogonal gene expression assay as a novel putative GR modulating chemical. Most active chemicals demonstrated profiles not associated with a known mechanism-of-action. However, many structurally related chemicals produced similar profiles, with exceptions such as diniconazole, whose profile differed from other active conazoles. Overall, the present study demonstrates how HTPP can be applied in screening-level chemical assessments through a series of examples and brief case studies.

Applying genomics in regulatory toxicology: a report of the ECETOC workshop on omics threshold on non-adversity.

In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC's activities in Omics have led to conceptual proposals for: (1) A framework that assures data quality for reporting and inclusion of Omics data in regulatory assessments; and (2) an approach to robustly quantify these data, prior to interpretation for regulatory use. In continuation of these activities this workshop explored and identified areas of need to facilitate robust interpretation of such data in the context of deriving points of departure (POD) for risk assessment and determining an adverse change from normal variation. ECETOC was amongst the first to systematically explore the application of Omics methods, now incorporated into the group of methods known as New Approach Methodologies (NAMs), to regulatory toxicology. This support has been in the form of both projects (primarily with CEFIC/LRI) and workshops. Outputs have led to projects included in the workplan of the Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) group of the Organisation for Economic Co-operation and Development (OECD) and to the drafting of OECD Guidance Documents for Omics data reporting, with potentially more to follow on data transformation and interpretation. The current workshop was the last in a series of technical methods development workshops, with a sub-focus on the derivation of a POD from Omics data. Workshop presentations demonstrated that Omics data developed within robust frameworks for both scientific data generation and analysis can be used to derive a POD. The issue of noise in the data was discussed as an important consideration for identifying robust Omics changes and deriving a POD. Such variability or "noise" can comprise technical or biological variation within a dataset and should clearly be distinguished from homeostatic responses. Adverse outcome pathways (AOPs) were considered a useful framework on which to assemble Omics methods, and a number of case examples were presented in illustration of this point. What is apparent is that high dimension data will always be subject to varying processing pipelines and hence interpretation, depending on the context they are used in. Yet, they can provide valuable input for regulatory toxicology, with the pre-condition being robust methods for the collection and processing of data together with a comprehensive description how the data were interpreted, and conclusions reached.

Combining phenotypic profiling and targeted RNA-Seq reveals linkages between transcriptional perturbations and chemical effects on cell morphology: Retinoic acid as an example.

The United States Environmental Protection Agency has proposed a tiered testing strategy for chemical hazard evaluation based on new approach methods (NAMs). The first tier includes in vitro profiling assays applicable to many (human) cell types, such as high-throughput transcriptomics (HTTr) and high-throughput phenotypic profiling (HTPP). The goals of this study were to: (1) harmonize the seeding density of U-2 OS human osteosarcoma cells for use in both assays; (2) compare HTTr- versus HTPP-derived potency estimates for 11 mechanistically diverse chemicals; (3) identify candidate reference chemicals for monitoring assay performance in future screens; and (4) characterize the transcriptional and phenotypic changes in detail for all-trans retinoic acid (ATRA) as a model compound known for its adverse effects on osteoblast differentiation. The results of this evaluation showed that (1) HTPP conducted at low (400 cells/well) and high (3000 cells/well) seeding densities yielded comparable potency estimates and similar phenotypic profiles for the tested chemicals; (2) HTPP and HTTr resulted in comparable potency estimates for changes in cellular morphology and gene expression, respectively; (3) three test chemicals (etoposide, ATRA, dexamethasone) produced concentration-dependent effects on cellular morphology and gene expression that were consistent with known modes-of-action, demonstrating their suitability for use as reference chemicals for monitoring assay performance; and (4) ATRA produced phenotypic changes that were highly similar to other retinoic acid receptor activators (AM580, arotinoid acid) and some retinoid X receptor activators (bexarotene, methoprene acid). This phenotype was observed concurrently with autoregulation of the RARB gene. Both effects were prevented by pre-treating U-2 OS cells with pharmacological antagonists of their respective receptors. Thus, the observed phenotype could be considered characteristic of retinoic acid pathway activation in U-2 OS cells. These findings lay the groundwork for combinatorial screening of chemicals using HTTr and HTPP to generate complementary information for the first tier of a NAM-based chemical hazard evaluation strategy.

Navigating Transcriptomic Connectivity Mapping Workflows to Link Chemicals with Bioactivities.

Screening new compounds for potential bioactivities against cellular targets is vital for drug discovery and chemical safety. Transcriptomics offers an efficient approach for assessing global gene expression changes, but interpreting chemical mechanisms from these data is often challenging. Connectivity mapping is a potential data-driven avenue for linking chemicals to mechanisms based on the observation that many biological processes are associated with unique gene expression signatures (gene signatures). However, mining the effects of a chemical on gene signatures for biological mechanisms is challenging because transcriptomic data contain thousands of noisy genes. New connectivity mapping approaches seeking to distinguish signal from noise continue to be developed, spurred by the promise of discovering chemical mechanisms, new drugs, and disease targets from burgeoning transcriptomic data. Here, we analyze these approaches in terms of diverse transcriptomic technologies, public databases, gene signatures, pattern-matching algorithms, and statistical evaluation criteria. To navigate the complexity of connectivity mapping, we propose a harmonized scheme to coherently organize and compare published workflows. We first standardize concepts underlying transcriptomic profiles and gene signatures based on various transcriptomic technologies such as microarrays, RNA-Seq, and L1000 and discuss the widely used data sources such as Gene Expression Omnibus, ArrayExpress, and MSigDB. Next, we generalize connectivity mapping as a pattern-matching task for finding similarity between a query (e.g., transcriptomic profile for new chemical) and a reference (e.g., gene signature of known target). Published pattern-matching approaches fall into two main categories: vector-based use metrics like correlation, Jaccard index, etc., and aggregation-based use parametric and nonparametric statistics (e.g., gene set enrichment analysis). The statistical methods for evaluating the performance of different approaches are described, along with comparisons reported in the literature on benchmark transcriptomic data sets. Lastly, we review connectivity mapping applications in toxicology and offer guidance on evaluating chemical-induced toxicity with concentration-response transcriptomic data. In addition to serving as a high-level guide and tutorial for understanding and implementing connectivity mapping workflows, we hope this review will stimulate new algorithms for evaluating chemical safety and drug discovery using transcriptomic data.

Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology.

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

Bioactivity screening of environmental chemicals using imaging-based high-throughput phenotypic profiling.

The present study adapted an existing high content imaging-based high-throughput phenotypic profiling (HTPP) assay known as "Cell Painting" for bioactivity screening of environmental chemicals. This assay uses a combination of fluorescent probes to label a variety of organelles and measures a large number of phenotypic features at the single cell level in order to detect chemical-induced changes in cell morphology. First, a small set of candidate phenotypic reference chemicals (n = 14) known to produce changes in the cellular morphology of U-2 OS cells were identified and screened at multiple time points in concentration-response format. Many of these chemicals produced distinct cellular phenotypes that were qualitatively similar to those previously described in the literature. A novel workflow for phenotypic feature extraction, concentration-response modeling and determination of in vitro thresholds for chemical bioactivity was developed. Subsequently, a set of 462 chemicals from the ToxCast library were screened in concentration-response mode. Bioactivity thresholds were calculated and converted to administered equivalent doses (AEDs) using reverse dosimetry. AEDs were then compared to effect values from mammalian toxicity studies. In many instances (68%), the HTPP-derived AEDs were either more conservative than or comparable to the in vivo effect values. Overall, we conclude that the HTPP assay can be used as an efficient, cost-effective and reproducible screening method for characterizing the biological activity and potency of environmental chemicals for potential use in in vitro-based safety assessments.

Testing for developmental neurotoxicity using a battery of in vitro assays for key cellular events in neurodevelopment.

Medium- to high-throughput in vitro assays that recapitulate the critical processes of nervous system development have been proposed as a means to facilitate rapid testing and identification of chemicals which may affect brain development. In vivo neurodevelopment is a complex progression of distinct cellular processes. Therefore, batteries of in vitro assays that model and quantify effects on a variety of neurodevelopmental processes have the potential to identify chemicals which may affect brain development at different developmental stages. In the present study, the results of concentration-response screening of 67 reference chemicals in a battery of high content imaging and microplate reader-based assays that evaluate neural progenitor cell proliferation, neural proginitor cell apoptosis, neurite initiation/outgrowth, neurite maturation and synaptogenesis are summarized and compared. The assay battery had a high degree of combined sensitivity (87%) for categorizing chemicals known to affect neurodevelopment as active and a moderate degree of combined specificity (71%) for categorizing chemicals not associated with affects on neurodevelopment as inactive. The combined sensitivity of the assay battery was higher compared to any individual assay while the combined specificity of the assay battery was lower compared to any individual assay. When selectivity of effects for a neurodevelopmental endpoint as compared to general cytotoxicity was taken into account, the combined sensitivity of the assay battery decreased (68%) while the combined specificity increased (93%). The identity and potency of chemicals identified as active varied across the assay battery, underscoring the need for use of a combination of diverse in vitro models to comprehensively screen chemicals and identify those which potentially affect neurodevelopment. Overall, these data indicate that a battery of assays which address many different processes in nervous system development may be used to identify potential developmental neurotoxicants and to distinguish specific from generalized cytotoxic effects with a high degree of success.

Lineage-dependent effects of aryl hydrocarbon receptor agonists contribute to liver tumorigenesis.

UNLABELLED: Rodent cancer bioassays indicate that the aryl hydrocarbon receptor (AHR) agonist, 2,3,7,8-tetracholorodibenzo-p-dioxin (TCDD), causes increases in both hepatocytic and cholangiocytic tumors. Effects of AHR activation have been evaluated on rodent hepatic stem cells (rHpSCs) versus their descendants, hepatoblasts (rHBs), two lineage stages of multipotent, hepatic precursors with overlapping but also distinct phenotypic traits. This was made possible by defining the first successful culture conditions for ex vivo maintenance of rHpScs consisting of a substratum of hyaluronans and Kubota's medium (KM), a serum-free medium designed for endodermal stem/progenitor cells. Supplementation of KM with leukemia inhibitory factor elicited lineage restriction to rHBs. Cultures were treated with various AHR agonists including TCDD, 6-formylindolo-[3,2-b]carbazole (FICZ), and 3-3'-diindolylmethane (DIM) and then analyzed with a combination of immunocytochemistry, gene expression, and high-content image analysis. The AHR agonists increased proliferation of rHpSCs at concentrations producing a persistent AHR activation as indicated by induction of Cyp1a1. By contrast, treatment with TCDD resulted in a rapid loss of viability of rHBs, even though the culture conditions, in the absence of the agonists, were permissive for survival and expansion of rHBs. The effects were not observed with FICZ and at lower concentrations of DIM. CONCLUSION: Our findings are consistent with a lineage-dependent mode of action for AHR agonists in rodent liver tumorigenesis through selective expansion of rHpSCs in combination with a toxicity-induced loss of viability of rHBs. These lineage-dependent effects correlate with increased frequency of liver tumors.

Aryl hydrocarbon receptor knockout rats are insensitive to the pathological effects of repeated oral exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin.

Sustained activation of the aryl hydrocarbon receptor (AHR) is believed to be the initial key event in AHR receptor-mediated tumorigenesis in the rat liver. The role of AHR in mediating pathological changes in the liver prior to tumor formation was investigated in a 4-week, repeated-dose study using adult female wild-type (WT) and AHR knockout (AHR-KO) rats treated with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Beginning at 8 weeks of age, AHR-KO and WT rats were dosed by oral gavage with varying concentrations of TCDD (0, 3, 22, 100, 300 and 1000 ng kg(-1) day(-1) ). Lung, liver and thymus histopathology, hematology, serum chemistry and the distribution of TCDD in liver and adipose tissue were examined. Treatment-related increases in the severity of liver and thymus pathology were observed in WT, but not AHR-KO rats. In the liver, these included hepatocellular hypertrophy, bile duct hyperplasia, multinucleated hepatocytes and inflammatory cell foci. A loss of cellularity in the thymic cortex and thymic atrophy was observed. Treatment-related changes in serum chemistry parameters were also observed in WT, but not AHR-KO rats. Finally, dose-dependent accumulation of TCDD was observed primarily in the liver of WT rats and primarily in the adipose tissue of AHR-KO rats. The results suggest that AHR activation is the initial key event underlying the progression of histological effects leading to liver tumorigenesis following TCDD treatment. Copyright © 2015 John Wiley & Sons, Ltd.

Transcriptomics-Based Points of Departure for Daphnia magna Exposed to 18 Per- and Polyfluoroalkyl Substances.

Per- and polyfluoroalkyl substances (PFAS) represent a large group of contaminants of concern based on their widespread use, environmental persistence, and potential toxicity. Many traditional models for estimating toxicity, bioaccumulation, and other toxicological properties are not well suited for PFAS. Consequently, there is a need to generate hazard information for PFAS in an efficient and cost-effective manner. In the present study, Daphnia magna were exposed to multiple concentrations of 22 different PFAS for 24 h in a 96-well plate format. Following exposure, whole-body RNA was extracted and extracts, each representing five exposed individuals, were subjected to RNA sequencing. Following analytical measurements to verify PFAS exposure concentrations and quality control on processed cDNA libraries for sequencing, concentration-response modeling was applied to the data sets for 18 of the tested compounds, and the concentration at which a concerted molecular response occurred (transcriptomic point of departure; tPOD) was calculated. The tPODs, based on measured concentrations of PFAS, generally ranged from 0.03 to 0.58 µM (9.9-350 µg/L; interquartile range). In most cases, these concentrations were two orders of magnitude lower than similarly calculated tPODs for human cell lines exposed to PFAS. They were also lower than apical effect concentrations reported for seven PFAS for which some crustacean or invertebrate toxicity data were available, although there were a few exceptions. Despite being lower than most other available hazard benchmarks, D. magna tPODs were, on average, four orders of magnitude greater than the maximum aqueous concentrations of PFAS measured in Great Lakes tributaries. Overall, this high-throughput transcriptomics assay with D. magna holds promise as a component of a tiered hazard evaluation strategy employing new approach methodologies. Environ Toxicol Chem 2024;00:1-16. © 2024 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates.

Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr). The tPOD calculation methods use data at the level of individual genes and gene set signatures, and compare data processed using the ToxCast Pipeline 2 (tcplfit2), BMDExpress and PLIER (Pathway Level Information ExtractoR). Methods were evaluated by comparing to in vitro PODs from a validated set of high-throughput screening (HTS) assays for a set of estrogenic compounds. Key findings include: (1) for a given chemical and set of experimental conditions, tPODs calculated by different methods can vary by several orders of magnitude; (2) tPODs are at least as sensitive to computational methods as to experimental conditions; (3) in comparison to an external reference set of PODs, some methods give generally higher values, principally PLIER and BMDExpress; and (4) the tPODs from HTTr in this one cell type are mostly higher than the overall PODs from a broad battery of targeted in vitro ToxCast assays, reflecting the need to test chemicals in multiple cell types and readout technologies for in vitro hazard screening.

Signature Analysis of High-Throughput Transcriptomics Screening Data for Mechanistic Inference and Chemical Grouping.

High-throughput transcriptomics (HTTr) uses gene expression profiling to characterize the biological activity of chemicals in in vitro cell-based test systems. As an extension of a previous study testing 44 chemicals, HTTr was used to screen an additional 1751 unique chemicals from the EPA's ToxCast collection in MCF7 cells using eight concentrations and an exposure duration of 6 hours. We hypothesized that concentration-response modeling of signature scores could be used to identify putative molecular targets and cluster chemicals with similar bioactivity. Clustering and enrichment analyses were conducted based on signature catalog annotations and ToxPrint chemotypes to facilitate molecular target prediction and grouping of chemicals with similar bioactivity profiles. Enrichment analysis based on signature catalog annotation identified known mechanisms-of-action (MeOAs) associated with well-studied chemicals and generated putative MeOAs for other active chemicals. Chemicals with predicted MeOAs included those targeting estrogen receptor (ER), glucocorticoid receptor (GR), retinoic acid receptor (RAR), the NRF2/KEAP/ARE pathway, AP-1 activation and others. Using reference chemicals for ER modulation, the study demonstrated that HTTr in MCF7 cells was able to stratify chemicals in terms of agonist potency, distinguish ER agonists from antagonists, and cluster chemicals with similar activities as predicted by the ToxCast ER Pathway model. Uniform manifold approximation and projection (UMAP) embedding of signature-level results identified novel ER modulators with no ToxCast ER Pathway model predictions. Finally, UMAP combined with ToxPrint chemotype enrichment was used to explore the biological activity of structurally-related chemicals. The study demonstrates that HTTr can be used to inform chemical risk assessment by determining in vitro points-of-departure, predicting chemicals' molecular mechanism(s)-of-action (MeOA) and grouping chemicals with similar bioactivity profiles.

Discovery Phase Agrochemical Predictive Safety Assessment Using High Content In Vitro Data to Estimate an In Vivo Toxicity Point of Departure.

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.

A Comparison of In Vitro Points of Departure with Human Blood Levels for Per- and Polyfluoroalkyl Substances (PFAS).

Per- and polyfluoroalkyl substances (PFAS) are widely used, and their fluorinated state contributes to unique uses and stability but also long half-lives in the environment and humans. PFAS have been shown to be toxic, leading to immunosuppression, cancer, and other adverse health outcomes. Only a small fraction of the PFAS in commerce have been evaluated for toxicity using in vivo tests, which leads to a need to prioritize which compounds to examine further. Here, we demonstrate a prioritization approach that combines human biomonitoring data (blood concentrations) with bioactivity data (concentrations at which bioactivity is observed in vitro) for 31 PFAS. The in vitro data are taken from a battery of cell-based assays, mostly run on human cells. The result is a Bioactive Concentration to Blood Concentration Ratio (BCBCR), similar to a margin of exposure (MoE). Chemicals with low BCBCR values could then be prioritized for further risk assessment. Using this method, two of the PFAS, PFOA (Perfluorooctanoic Acid) and PFOS (Perfluorooctane Sulfonic Acid), have BCBCR values < 1 for some populations. An additional 9 PFAS have BCBCR values < 100 for some populations. This study shows a promising approach to screening level risk assessments of compounds such as PFAS that are long-lived in humans and other species.

Knockout of the aryl hydrocarbon receptor results in distinct hepatic and renal phenotypes in rats and mice.

The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor which plays a role in the development of multiple tissues and is activated by a large number of ligands, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). In order to examine the roles of the AHR in both normal biological development and response to environmental chemicals, an AHR knockout (AHR-KO) rat model was created and compared with an existing AHR-KO mouse. AHR-KO rats harboring either 2-bp or 29-bp deletion mutation in exon 2 of the AHR were created on the Sprague-Dawley genetic background using zinc-finger nuclease (ZFN) technology. Rats harboring either mutation type lacked expression of AHR protein in the liver. AHR-KO rats were also insensitive to thymic involution, increased hepatic weight and the induction of AHR-responsive genes (Cyp1a1, Cyp1a2, Cyp1b1, Ahrr) following acute exposure to 25 µg/kg TCDD. AHR-KO rats had lower basal expression of transcripts for these genes and also accumulated ~30-45-fold less TCDD in the liver at 7 days post-exposure. In untreated animals, AHR-KO mice, but not AHR-KO rats, had alterations in serum analytes indicative of compromised hepatic function, patent ductus venosus of the liver and persistent hyaloid arteries in the eye. AHR-KO rats, but not AHR-KO mice, displayed pathological alterations to the urinary tract: bilateral renal dilation (hydronephrosis), secondary medullary tubular and uroepithelial degenerative changes and bilateral ureter dilation (hydroureter). The present data indicate that the AHR may play significantly different roles in tissue development and homeostasis and toxicity across rodent species.

Neurotrophic effects of leukemia inhibitory factor on neural cells derived from human embryonic stem cells.

Various growth factor cocktails have been used to proliferate and then differentiate human neural progenitor (NP) cells derived from embryonic stem cells (ESC) for in vitro and in vivo studies. However, the cytokine leukemia inhibitory factor (LIF) has been largely overlooked. Here, we demonstrate that LIF significantly enhanced in vitro survival and promoted differentiation of human ESC-derived NP cells. In NP cells, as well as NP-derived neurons, LIF reduced caspase-mediated apoptosis and reduced both spontaneous and H2O2-induced reactive oxygen species in culture. In vitro, NP cell proliferation and the yield of differentiated neurons were significantly higher in the presence of LIF. In NP cells, LIF enhanced cMyc phosphorylation, commonly associated with self-renewal/proliferation. Also, in differentiating NP cells LIF activated the phosphoinositide 3-kinase and signal transducer and activator of transcription 3 pathways, associated with cell survival and reduced apoptosis. When differentiated in LIF+ media, neurite outgrowth and ERK1/2 phosphorylation were potentiated together with increased expression of gp130, a component of the LIF receptor complex. NP cells, pretreated in vitro with LIF, were effective in reducing infarct volume in a model of focal ischemic stroke but LIF did not lead to significantly improved initial NP cell survival over nontreated NP cells. Our results show that LIF signaling significantly promotes human NP cell proliferation, survival, and differentiation in vitro. Activated LIF signaling should be considered in cell culture expansion systems for future human NP cell-based therapeutic transplant studies.