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      A Modern Genotoxicity Testing Paradigm: Integration of the High-Throughput CometChip® and the TGx-DDI Transcriptomic Biomarker in Human HepaRG™ Cell Cultures

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          Abstract

          Higher-throughput, mode-of-action-based assays provide a valuable approach to expedite chemical evaluation for human health risk assessment. In this study, we combined the high-throughput alkaline DNA damage-sensing CometChip ® assay with the TGx-DDI transcriptomic biomarker (DDI = DNA damage-inducing) using high-throughput TempO-Seq ®, as an integrated genotoxicity testing approach. We used metabolically competent differentiated human HepaRG™ cell cultures to enable the identification of chemicals that require bioactivation to cause genotoxicity. We studied 12 chemicals (nine DDI, three non-DDI) in increasing concentrations to measure and classify chemicals based on their ability to damage DNA. The CometChip ® classified 10/12 test chemicals correctly, missing a positive DDI call for aflatoxin B1 and propyl gallate. The poor detection of aflatoxin B1 adducts is consistent with the insensitivity of the standard alkaline comet assay to bulky lesions (a shortcoming that can be overcome by trapping repair intermediates). The TGx-DDI biomarker accurately classified 10/12 agents. TGx-DDI correctly identified aflatoxin B1 as DDI, demonstrating efficacy for combined used of these complementary methodologies. Zidovudine, a known DDI chemical, was misclassified as it inhibits transcription, which prevents measurable changes in gene expression. Eugenol, a non-DDI chemical known to render misleading positive results at high concentrations, was classified as DDI at the highest concentration tested. When combined, the CometChip ® assay and the TGx-DDI biomarker were 100% accurate in identifying chemicals that induce DNA damage. Quantitative benchmark concentration (BMC) modeling was applied to evaluate chemical potencies for both assays. The BMCs for the CometChip ® assay and the TGx-DDI biomarker were highly concordant (within 4-fold) and resulted in identical potency rankings. These results demonstrate that these two assays can be integrated for efficient identification and potency ranking of DNA damaging agents in HepaRG™ cell cultures.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Modern Applied Statistics with S

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              Rank Transformations as a Bridge between Parametric and Nonparametric Statistics

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                Author and article information

                Contributors
                Journal
                Front Public Health
                Front Public Health
                Front. Public Health
                Frontiers in Public Health
                Frontiers Media S.A.
                2296-2565
                18 August 2021
                2021
                : 9
                : 694834
                Affiliations
                [1] 1Environmental Health Science and Research Bureau, Health Canada , Ottawa, ON, Canada
                [2] 2Integrated Laboratory Systems Inc. (ILS), Research Triangle Park , Durham, NC, United States
                [3] 3National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park , Durham, NC, United States
                [4] 4Department of Biological Engineering, Massachusetts Institute of Technology , Cambridge, MA, United States
                [5] 5Department of Biology, University of Ottawa , Ottawa, ON, Canada
                Author notes

                Edited by: Manosij Ghosh, KU Leuven, Belgium

                Reviewed by: Djaltou Aboubaker Osman, Center of Study and Research of Djibouti (CERD), Ethiopia; Birgit Mertens, Sciensano, Belgium

                *Correspondence: Carole L. Yauk Carole.Yauk@ 123456uottawa.ca

                This article was submitted to Environmental health and Exposome, a section of the journal Frontiers in Public Health

                Article
                10.3389/fpubh.2021.694834
                8416458
                34485225
                bca9c6a0-4871-4442-b311-27d57ad688c0
                Copyright © 2021 Her Majesty the Queen in Right of Canada.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 13 April 2021
                : 14 July 2021
                Page count
                Figures: 4, Tables: 4, Equations: 0, References: 107, Pages: 19, Words: 14559
                Funding
                Funded by: Health Canada 10.13039/501100000008
                Award ID: Genomics Research and Development Initiative
                Funded by: University of Ottawa 10.13039/100008572
                Award ID: Canada Research Chairs Program
                Categories
                Public Health
                Original Research

                genetic toxicology,tgx-ddi genomic biomarker,tgx-28.65 genomic biomarker,metabolic activation,toxicogenomics,human health risk assessment

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