High-throughput Transcriptomics Screen of 137 Per- and Polyfluoroalkyl Substances (PFAS) in U-2 OS Cells
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE297135 | GEO | 2025/06/17
REPOSITORIES: GEO
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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:Understanding the mechanisms by which environmental chemicals cause toxicity is necessary for effective human health risk assessment. High-Throughput Transcriptomics (HTTr) can be used to inform risk assessment on toxicological mechanisms, hazards, and potencies. We applied HTTr to elucidate the molecular mechanisms by which Per- and Polyfluoroalkyl Substances (PFAS) cause liver toxicity. We contrasted transcriptomic profiles of four prototype PFAS against transcriptomic profiles from liver-toxic and non-liver-toxic reference compounds, alongside chemicals that activate peroxisome proliferator-activated receptors (PPARs). Our analysis was conducted on metabolically competent 3-D human liver spheroids produced from primary cells of 10 donors. Pathway analysis showed that PFOS and PFDS perturb many of the same pathways as the liver-toxic compounds in the spheroids, and that the cholesterol biosynthesis pathways are significantly affected by exposure to these compounds. PFOA alters lipid metabolism-related pathways but its expression profile does not closely match reference compounds. PFBS upregulates many degradation-related pathways and targets many of the same pathways as the PPAR agonists and acetaminophen. Our transcriptional analysis does not support that these PFAS are DNA damaging in this model. A multidimensional scaling analysis revealed that PFOS, PFOA, and PFDS cluster together in the same 3-D space as liver-damaging compounds; whereas, PFBS clusters more closely with the non-liver-damaging compounds. Benchmark concentration-response modeling predicts that all the PFAS are sufficiently bioactive to be liver-toxic. Overall, our results show that these PFAS produce unique transcriptional changes as well as altering pathways associated with established liver-toxic chemicals in this liver spheroid model.
2025-02-17 | GSE272576 | 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 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: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:Per- and polyfluoroalkyl substances (PFAS) are some of the most prominent organic contaminants in human blood that have the potential to disrupt biological processes and pathways in the liver. Although the toxicological implications from human exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) are well established, data on other, lesser-understood PFAS are limited. A challenge for regulatory authorities is to determine acceptable levels of human exposure to large, diverse classes of environmental contaminants. New approach methodologies (NAMs) that apply bioinformatics tools to interpret biological data are being increasingly considered to inform risk assessment when traditional toxicology methodologies are not amenable. The aim of the current investigation was to identify the biological responses relevant to PFAS mode of action as the concentration (benchmark dose) that these effects take place in order to utililze this information to inform/facilitate read-across for risk assessment of data-poor PFAS. A TempO-Seq platform (BioSpyder) measured gene expression changes in human liver microtissues (i.e., spheroids) after 1-day and 10-day exposures to increasing concentrations of PFAS. A bioinformatics framework was applied to 23 PFAS sub-classed into carboxylates (PFCAs), sulfonates (PFSAs), or PFAS precursors that were analyzed for the total altered transcripts, the concentration where effects take place, and identifying target genes of interest. Both PFCAs and PFSAs exhibited a trend toward increased transcriptional changes with carbon chain-length. Specifically, longer-chain compounds (7 to 10 carbons) were more likely to surpass liver-toxic transcriptomic thresholds established from previous studies than shorter chain PFAS. Longer-chain PFAS were also more potent, inducing transcriptional effects at lower concentrations. However, PFOS was the most potent PFAS and of all precursors, only PFOSA (a PFOS precursor) induced a response. The combined high-throughput transcriptomic and bioinformatics analyses revealed the capability of NAMs to assess the effects of PFAS in liver microtissues; such data improves our understanding of PFAS-related effects in humans and facilitates the use of read-across in human health risk assessment for other data-poor chemicals.
2021-11-08 | GSE145239 | GEO
Project description:This study set out to evaluate the hypothesis that PFAS exposure alters EV regulation via upstream molecular mediators of EV-based alterations through cellular transcriptomics assessment in a concentration-response manner. To evaluate this hypothesis, HepG2 liver cells were treated in concentration-response with individual PFOS, PFOA, or PFHxA, in addition to an equimolar PFAS mixture. Global gene expression was measured. These analyses set out to evaluate concentration-dependent changes in mRNA signatures within HepG2 immortalized liver cells exposed to individual PFOS, PFOA, PFHxA or an equimolar mixture containing all three PFAS.
2025-04-08 | GSE266866 | GEO
Project description:The per-and polyfluoroalkyl substances (PFAS) are of significant global concern due to their highly ubiquitous and persistent nature, bioaccumulation in organisms, and potential toxicity. The aquatic environment is known as an important sink for PFAS resulting in high concentrations in aquatic organisms. However, little is known about the developmental windows of sensitivity in which the PFAS chemicals are biologically active, in addition to the toxicity endpoints that best reflect chemical hazard. In this study, zebrafish (Danio rerio) were exposed to a 0.33% DMSO vehicle control, 1uM chlorpyrifos (CAS 2921-88-2) positive control, and eight concentrations (0-100 uM, half-log dilutions) of three environmentally relevant PFAS compounds in concentration-response: PFOS (CAS 1763-21-1), PFOA (CAS 45285-51-6), and PFHxS (CAS 355-46-4). There was also a group of unexposed zebrafish aliquoted from a single pool into all exposure plates to serve as a quality assurance measure. The goal of this study was to generate transcriptomic point of departure (tPOD; a benchmark dose/concentration -based treatment level below which a concerted gene expression response is not observed) estimates for zebrafish exposed to PFAS compounds as a health protective exposure level for risk assessment. Through the use of short-term embryo/larval plate-based high-throughput toxicity tests, tPODs were determined across seven distinct developmental windows (6-24 hours post fertilization (hpf), 6-48 hpf, 24-48 hpf, 6-120 hpf, 24-120 hpf, 48-120 hpf, 96-120 hpf) to assess how common experimental design variables (e.g., different exposure durations, exposure at different developmental stages) affect point of departure estimates.
2024-08-28 | GSE242402 | 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
Project description:An arrayed library containing pooled siRNAs targeting 18,480 human genes (Dharmacon, Lafayette, CO) was screened as previously described (Roosing et al., 2015).Briefly, 384-well plates with optical bottom (Greiner Bio-One, Monroe, NC) were spotted with 1 μl of 0.5 μM siRNA. Reverse transfection was next performed using Lipofectamine RNAiMAX at the final siRNA concentration of 10 nM. Culture medium was replaced with DMEM 24 hrs after transfection and cells were incubated for additional 48 hrs before lysis in SDS buffer for downstream analysis. These siRNAs were distributed in 57 plates, and after screen, we pooled 4 bar-coded plates for sequencing per Illumina sequencing lane.
2022-07-01 | GSE207344 | GEO