Project description: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.
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.
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).
Project description:The toxicity and potential associated molecular mechanism of a reference cigarette, 3R4F and a prototypic modified risk tobacco products ((p)MRTP) were investigated with human bronchial epithelial cells using high-throughput screening and whole transcriptomics analysis.
Project description:The toxicity and potential associated molecular mechanism of a reference cigarette, 3R4F and THS2.2 a candidate modified risk tobacco products ((p)MRTP) were investigated with human bronchial epithelial cells using high-throughput screening and whole transcriptomics analysis.
Project description:The toxicity and potential associated molecular mechanism of a mixture of representative flavors, compared to a matrix containing propylene glicol (PG), vegetable glycerin (VG) and nicotine, were investigated with human bronchial epithelial cells using high-throughput screening and whole transcriptomics analysis.
Project description:To identify novel therapeutic opportunities for patients with acquired resistance to endocrine treatments in breast cancer, we applied high-throughput screening to explore currently marketed drugs. The Ec50 values were determined for MCF7 and LTED cell lines to identify the compounds showing higher inhibition of LTED cells. The best compound was YC-1 and gene microarray studies were done in vitro for mechanistic exploration. MCF7 and LTED cells were treated with YC-1 for RNA extraction and hybridization on Affymetrix microarrays.
