High-throughput Toxicogenomic Screening of Chemicals in the Environment Using Metabolically Competent, Human-derived Hepatic Cell Cultures

Gene expression data from the Fluidigm qRT-PCR arrays was analyzed in R (v3.6.1; R Foundation for Statistical Computing, 2019). Prior to processing through the tcpl package, each qRT-PCR primer set was annotated as an individual assay endpoint (aeid) for analyses. For each plate, well types were designated for test compound wells (t), positive controls (c), (that is phenobarbital) and neutral controls (n, DMSO). Fold-change in the number of amplification cycles needed to pass the background threshold (Ct) for 96 transcripts to (ftp://newftp.epa.gov/COMPTOX/CCTE_Publication_Data/CCED_Publication_Data/Wambaugh/ToxCast_LTEA, file LTEA_Level2_20191119.zip) were normalized to the geometric mean of three housekeeping genes (ACTB, GAPDH, POLR2A) to generate ΔCt values (cval). Prior to calculating the response values (rval), or ΔΔCt, for each transcript (n = 96) per well, the baseline value (bval), the plate-wise median of the neutral control wells, was generated for each plate (the normalization process is described in detail in supplemental file SupFile4-DeltaCTCalculation.docx). The bval was subtracted from the cval to yield the rval or log2 Fold Change per transcript. 

Gene expression data from the Fluidigm qRT-PCR arrays was analyzed in R (v3.6.1; R Foundation for Statistical Computing, 2019). Prior to processing through the tcpl package, each qRT-PCR primer set was annotated as an individual assay endpoint (aeid) for analyses. For each plate, well types were designated for test compound wells (t), positive controls (c), (that is phenobarbital) and neutral controls (n, DMSO). Fold-change in the number of amplification cycles needed to pass the background threshold (Ct) for 96 transcripts to (ftp://newftp.epa.gov/COMPTOX/CCTE_Publication_Data/CCED_Publication_Data/Wambaugh/ToxCast_LTEA, file LTEA_Level5_20191119.zip) were normalized to the geometric mean of three housekeeping genes (ACTB, GAPDH, POLR2A) to generate ΔCt values (cval). Prior to calculating the response values (rval), or ΔΔCt, for each transcript (n = 96) per well, the baseline value (bval), the plate-wise median of the neutral control wells, was generated for each plate (the normalization process is described in detail in supplemental file SupFile4-DeltaCTCalculation.docx). The bval was subtracted from the cval to yield the rval or log2 Fold Change per transcript.

Supplemental File LTEA_Inucyte_Images.zip is comprised of 20,493 images totaling more than 15 gigabytes. Cell morphology images were acquired for each well/plate with an Essen IncuCyte™ FLR automated phase-contrast microscope located inside a tissue culture incubator. Six 96-well culture plates were loaded into the instrument and imaged for an elapsed time (~24 minutes). The IncuCyte™ software was used for image capturing and export of images in JPEG format. 

This dataset is associated with the following publication:
Franzosa, J., J. Bonzo, J. Jack, N.C. Baker, P. Kothiya, R. Witek, P. Hurban, S. Siferd, S. Hester, I. Shah, S. Ferguson, K. Houck, and J. Wambaugh. High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures.   npj Systems Biology and Applications. Springer Nature Group, New York, NY,  7: Article 7, (2021).

Tags: bayesian-statistics, chemical-evaluation, hepatotoxicity, high-throughput-screening, high-throughput-transcriptomic-screening, high-throughput-transcriptomics, human-hepatocytes, in-vitro-hepatic-metabolism, in-vitro-high-throughput-screening, qpcr, toxcast, toxcast-database, transcriptomics
Organization: U.S. Environmental Protection Agency