High-Throughput Transcriptomics Analysis of Chemical Effects on Zebrafish Liver (ZFL) and Embryonic (ZEM2S) Cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Danio rerio
PROVIDER: GSE302987 | GEO | 2025/09/17
REPOSITORIES: GEO
Similar Datasets
Project description:With thousands of chemicals in commerce and the environment, rapid identification of potential hazards is a critical need. Combining broad molecular profiling with targeted in vitro assays, such as high-throughput transcriptomics (HTTr) and receptor screening assays, could improve identification of chemicals that perturb key molecular targets associated with adverse outcomes. We aimed to link transcriptomic readouts to individual molecular targets and integrate transcriptomic predictions with orthogonal receptor-level assays in a proof-of-concept framework for chemical hazard prioritization. Transcriptomic profiles generated via TempO-Seq in U-2 OS and HepaRG cell lines were used to develop signatures comprised of genes uniquely responsive to reference chemicals for distinct molecular targets. These signatures were applied to 75 reference and 1,126 non-reference chemicals screened via HTTr in both cell lines. Selective bioactivity towards each signature was determined by comparing potency estimates against the bulk of transcriptomic bioactivity for each chemical. Chemicals predicted by transcriptomics were confirmed for target bioactivity and selectivity using available orthogonal assay data from US EPA’s ToxCast program. A subset of 37 selectively acting chemicals from HTTr that did not have sufficient orthogonal data were prospectively tested using one of five receptor-level assays. Of the 1,126 non-reference chemicals screened, 201 demonstrated selective bioactivity in at least one transcriptomic signature, and 57 were confirmed as selective nuclear receptor agonists. Chemicals bioactive for each signature were significantly associated with orthogonal assay bioactivity, and signature-based points-of-departure were equally or more sensitive than biological pathway altering concentrations in 81.2% of signature-prioritized chemicals. Prospective profiling found that 18 of 37 (49%) chemicals without prior orthogonal assay data were bioactive against the predicted receptor. Our work demonstrates that integrating transcriptomics with targeted orthogonal assays in a tiered framework can support Next Generation Risk Assessment by informing putative molecular targets and prioritizing chemicals for further testing. NOTE: this GEO entry only includes the HepaRG cell line data; the U-2 OS cell line data can be located via GEO accession number GSE274318.
2025-03-25 | GSE284321 | GEO
Project description: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.
2024-08-20 | GSE272548 | GEO
Project description: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, 1,201 test chemicals were screened for bioactivity at eight concentrations using a 24-hour 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.
2024-08-20 | GSE274318 | GEO
Project description:High-throughput profiling assays such as high-throughput phenotypic profiling (HTPP) with Cell Painting and high-throughput transcriptomics (HTTr) with TempO-SeqTM are new approach methods that have been used to characterize the bioactivity and potential hazards of chemicals. To better account for potential in vivo hazards in screening, we previously coupled both assays to an in vitro metabolism platform, Alginate Immobilization of Metabolic Enzymes (AIME). In this study, we expanded upon our previous results in estrogenic reference chemicals by screening an additional 40 chemicals in VM7Luc4E2 breast cells anticipated to have varied activity and/or shifts in activity with metabolism in an estrogen receptor transactivation assay (ERTA) using the AIME platform. Our results demonstrate how HTTr could detect ER activity and the influence of metabolism on estrogenicity through the activation of ER high-confidence (ERHC) gene signatures and metabolism-induced shifts in ERHC signature enrichment. Additionally, HTPP could detect cases where metabolism impacted chemical cytotoxicity and detect generation of metabolites that were bioactive in a different way than their respective parent compounds when comparing the profiles of active features between AIME conditions. Notably, our findings highlighted examples of chemicals that had very different phenotypic and gene expression profiles between metabolic conditions that would not be observed in traditional chemical screening in most cell models. This study exhibited how high-throughput profiling assays could distinguish changes in bioactivity with metabolic competence using the AIME platform, which will ultimately better inform next generation risk assessment by providing more comprehensive hazard characterizations.
2025-06-10 | GSE296915 | GEO
Project description:High-throughput transcriptomics (HTTr) was undertaken to quantify and characterize the biological effects of chemicals observed in human-derived in vitro test systems. A set of 137 structurally diverse PFAS was tested using the HTTr assay in the human-derived cell type U-2 OS (osteosarcoma). The PFAS studies were carried out as a part of a larger screening study of a total of 1323 chemicals. Chemicals were randomized to treatment plates (cells plus media) in triplicate. Plates also contained reference treatments for quality control purposes. The TempO-Seq human whole transcriptome assay (Yeakley et al., 2017) was used to identify biological pathway altering concentrations (BPACs) and characterize the biological activity of test chemicals. For this analysis, a catalog of 11,037 gene expression signatures collated from multiple public sources were analyzed using concentration-response modeling of signature enrichment scores determined using single-sample gene set enrichment analysis (ssGSEA) (Barbie et al. 2009) with DESeq2-moderated fold change values as input (Love et al. 2014). A sample was considered active if 25 or more signatures were concentration-responsive and the BPAC was calculated as the 5th percentile of benchmark concentrations (BMCs) of active signatures.
2025-06-17 | GSE297135 | GEO
Project description: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).
2023-12-05 | GSE249377 | GEO
Project description:Since initial regulatory action in 2010 in Canada, bisphenol A (BPA) has been progressively replaced by structurally related alternative chemicals. Unfortunately, many of these chemicals are data-poor, limiting toxicological risk assessment. We used high-throughput transcriptomics to evaluate potential hazards and compare potencies of BPA and 15 BPA alternative chemicals in cultured breast cancer cells. MCF-7 cells were exposed to BPA and 15 alternative chemicals (0.0005 – 100 µM) for 48 hrs. TempO-Seq sequencing (BioSpyder Inc.) was used to examine general toxicological effects and estrogen receptor alpha (ERα)-associated transcriptional changes. Benchmark concentration (BMC) analysis was conducted to identify two global transcriptomic points of departure (tPODs): (a) the lowest pathway median gene BMC and (b) the 25th lowest rank-ordered gene BMC. ERα activation was evaluated using a published transcriptomic biomarker and an ERα-specific tPOD was derived. Genes fitting BMC models were subjected to upstream regulator and canonical pathway analysis in Ingenuity Pathway Analysis. Biomarker analysis identified BPA and eight alternative chemicals as ERα active. Global and ERα tPODs produced highly similar potency rankings with BPAF as the most potent chemical tested, followed by BPA, BPC, 4,4’-BPF, BPAP, BPS, BADGE, 2,4’-BPF, Pergafast201®, D-8, 2,4’-BPS, TGSA, and BPS-MAE. Further, BPA and transcriptionally active alternative chemicals enriched similar gene sets associated with increased cell division and cancer-related processes. These data provide support for future read-across applications of transcriptomic profiling for risk assessment of data-poor chemicals and suggest that several BPA alternative chemicals may cause hazards at similar concentrations to BPA.
2022-08-18 | GSE211183 | GEO
Project description:One limitation of previous high-throughput transcriptomics (HTTr) chemical screening studies using TempO-Seq is that most of the in vitro models used on those studies lack instrinsic capabilites to metabolize xenobiotics. This study incorporated an in vitro metabolism platform, aliginate immobilization of metabolic enzymes (AIME), into the dosing procedures for HTTr screening to address this limitation. The 384-well, lid-based platform is incubated for 2 hours on standard microplates containing chemicals, metabolic co-factors and cell culture medium to make "conditioned" medium. This medium is used to treat cells rather than treated them with parent chemicals directly, and the AIME platform does not impact downstream procedures for preparation of cell lysates that are compatible with the TempO-Seq assay. The AIME platform was used concurrently in negative or "nomet" (water + alginate) and positive or "met" (hepatic S9 + alginate) metabolic conditions. This proof-of-concept experiment screened three previously studied estrogenic reference chemicals representing three "shifts" with metabolism in the VM7Luc4E2 breast cell line in an estrogen receptor transactivation assay: bioinactivation, bioactivation or no change with metabolism. Our results indicated that the TempO-Seq assay could detect changes in bioactivity with metabolism. The established workflow can be used in future studies to improve human relevance in our chemical screening efforts.
2025-04-29 | GSE292777 | GEO
Project description:New approach methodologies (NAMs) that efficiently provide information about chemical hazard without using whole animals are needed to accelerate the pace of chemical safety assessments. Technological advancements in gene expression assays have made in vitro high-throughput transcriptomics (HTTr) a feasible option for NAMs-based hazard characterization of environmental chemicals. In the present study, we evaluated the Templated Oligo with Sequencing Readout (TempO-Seq) assay for HTTr concentration-response screening of a small set of chemicals in the human-derived MCF7 cell model. Our experimental design included a variety of reference samples and reference chemical treatments in order to objectively evaluate TempO-Seq assay performance. To facilitate analysis of these data, we developed a robust and scalable bioinformatics pipeline using open-source tools. We also developed a novel gene expression signature-based concentration-response modeling approach and compared the results to a previously implemented workflow for concentration-response analysis of transcriptomics data using BMDExpress. Analysis of reference samples and reference chemical treatments demonstrated highly reproducible differential gene expression signatures. In addition, we found that aggregating signals from individual genes into gene signatures prior to concentration-response modeling yielded in vitro transcriptional biological pathway altering concentrations (BPACs) that were closely aligned with previous ToxCast high-throughput screening (HTS) assays. Often these identified signatures were associated with the known molecular target of the chemicals in our test set as the most sensitive components of the overall transcriptional response. This work has resulted in a novel and scalable in vitro HTTr workflow that is suitable for high throughput hazard evaluation of environmental chemicals.
2021-01-25 | GSE162855 | GEO
Project description: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.
2022-04-18 | GSE200845 | GEO