Unknown,Transcriptomics,Genomics,Proteomics

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Interlaboratory study to determine the reproducibility of toxicogenomics datasets

ABSTRACT: The application of toxicogenomics as a predictive tool for chemical risk assessment has been under evaluation by the toxicology community for more than a decade. However, toxicogenomics predominately remains a tool for investigative research rather than for regulatory risk assessment. In this study, we aimed to determine whether the current generation of microarray technology in combination with an in vitro experimental design was capable of generating robust, reproducible data of sufficient quality to show promise as a tool for regulatory risk assessment. To this end, we designed a prospective collaborative study to determine the level of inter- and intra-laboratory reproducibility between three independent laboratories. All test sites adopted the same protocols for all aspects of the toxicogenomic experiment including cell culture, chemical exposure, RNA extraction, microarray data generation and analysis. As a case study, the genotoxic carcinogen B[a]P and the human hepatocyte cell line HepG2 were used to generate three comparable toxicogenomic data sets. High levels of technical reproducibility were demonstrated using a widely employed gene expression microarray platform. While differences at the global transcriptome level were still observed between the test sites, a common subset of B[a]P responsive genes was identified across all test sites which included both genes previously reported in the literature as B[a]P responsive in addition to the same most highly up and down regulated genes. Pending further analysis, these preliminary data show promise that the current generation of microarray technology in combination with a standard in vitro experimental design can produce robust data that can be reproducibly generated in independent laboratories. Future work will need to determine whether in vitro model(s) can be not only reproducible but also predictive for a range of toxic chemicals with different mechanisms of action. Such an approach may potentially be part of future in vitro testing regimes for regulatory risk assessment. The aim of this study was to evaluate the inter- and intra-laboratory reproducibility of toxicogenomics data for toxicity testing in a regulatory setting. 3 Test Centres performed the same experimental protocol treating HepG2 cells with 3 mM Benzo[a]pyrene (B[a]P) (in 0.5% DMSO) for 24 hours prior to RNA extraction and microarray analysis. Three biological replicates of B[a]P and DMSO treatments were analysed by microarray analysis in each Test Centre. Two Test Centres analysed one sample in triplicate to determine technical reproducibility of the chosen array platform. One Centre analysed two samples in duplicate. 24 samples in total were used in this study

ORGANISM(S): Homo sapiens

SUBMITTER: Yeyejide Adeleye

PROVIDER: E-GEOD-25936 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:The application of toxicogenomics as a predictive tool for chemical risk assessment has been under evaluation by the toxicology community for more than a decade. However, toxicogenomics predominately remains a tool for investigative research rather than for regulatory risk assessment. In this study, we aimed to determine whether the current generation of microarray technology in combination with an in vitro experimental design was capable of generating robust, reproducible data of sufficient quality to show promise as a tool for regulatory risk assessment. To this end, we designed a prospective collaborative study to determine the level of inter- and intra-laboratory reproducibility between three independent laboratories. All test sites adopted the same protocols for all aspects of the toxicogenomic experiment including cell culture, chemical exposure, RNA extraction, microarray data generation and analysis. As a case study, the genotoxic carcinogen B[a]P and the human hepatocyte cell line HepG2 were used to generate three comparable toxicogenomic data sets. High levels of technical reproducibility were demonstrated using a widely employed gene expression microarray platform. While differences at the global transcriptome level were still observed between the test sites, a common subset of B[a]P responsive genes was identified across all test sites which included both genes previously reported in the literature as B[a]P responsive in addition to the same most highly up and down regulated genes. Pending further analysis, these preliminary data show promise that the current generation of microarray technology in combination with a standard in vitro experimental design can produce robust data that can be reproducibly generated in independent laboratories. Future work will need to determine whether in vitro model(s) can be not only reproducible but also predictive for a range of toxic chemicals with different mechanisms of action. Such an approach may potentially be part of future in vitro testing regimes for regulatory risk assessment.

Project description:Environmental risk assessment relies heavily on the use of bioassays to assess the environmental impact of chemicals. Gene expression is gaining acceptance as a valuable mechanistic endpoint in bioassays and effect-based screening. Data analysis and its results however, are often complex and not directly applicable in risk assessment. Classifier analysis is a promising method to turn complex gene expression analysis results into answers suitable for risk assessment. We have assembled a large gene expression dataset assembled from multiple studies and experiments in the springtail Folsomia candida, with the aim of selecting a set of genes that can be trained to classify general toxic stress. By performing differential expression analysis prior to classification we were able to select a set of 135 genes which was enriched in stress related processes. This set was then used to classify two test sets comprised of chemical spiked soils, polluted soils and clean soils and compared to another, more traditional feature selection for classification. The gene set presented here outperformed the more traditionally selected gene set. This gene set has the potential to be used as a biomarker to test for adverse effects caused by chemicals in springtails to provide endpoints in environmental risk assessment. The data presented in our manuscript is part of a larger experiment which was performed in single, large loop design. Only the samples used in the study presented here are named while the other samples will remain unnamed. All the data can still be used for normalization after which the analysis presented in the manuscript can be replicated. A single channel, interwoven loop design was used to test animals exposed to a control and to 5 concentrations of cadmium and phenanthrene (cadmium concentrations are: cad_1 till cad_5: 5.8, 14.5, 28.9, 57.9 and 115.8 mg/Kg respectively and phenanthrene concentrations are: phe_1 till Phe_5: 0, 4.6, 11.4, 22.9, 45.8 and 91.6 mg/Kg soil respectively). Exposures lasted for 2 days and used 4 biological replicates per condition each containing 30 grams soil and 30 individuals.

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Interlaboratory study to determine the reproducibility of toxicogenomics datasets

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