Danyel Jennen

Comparison of HepG2 and HepaRG by Whole-Genome Gene Expression Analysis for the Purpose of Chemical Hazard Identification

Direct comparison of the hepatoma cell lines HepG2 and HepaRG has previously been performed by only evaluating a limited set of genes or proteins. In this study, we examined the whole-genome gene expression of both cell lines before and after exposure to the genotoxic (GTX) carcinogens aflatoxin B1 and benzo[a]pyrene and the nongenotoxic (NGTX) carcinogens cyclosporin A, 17beta-estradiol, and 2,3,7,8-tetrachlorodibenzo-para-dioxin for 12 and 48 h. Before exposure, this analysis revealed an extensive network of genes and pathways, which were regulated differentially for each cell line. The comparison of the basal gene expression between HepG2, HepaRG, primary human hepatocytes (PHH), and liver clearly showed that HepaRG resembles PHH and liver the most. After exposure to the GTX and NGTX carcinogens, for both cell lines, common pathways were found that are important in carcinogenesis, for example, cell cycle regulation and apoptosis. However, also clear differences between exposed HepG2 and HepaRG were observed, and these are related to common metabolic processes, immune response, and transcription processes. Furthermore, HepG2 performs better in discriminating between GTX and NGTX carcinogens. In conclusion, these results have shown that HepaRG is a more suited in vitro liver model for biological interpretations of the effects of exposure to chemicals, whereas HepG2 is a more promising in vitro liver model for classification studies using the toxicogenomics approach. Although, it should be noted that only five carcinogens were used in this study.

An untargeted multi-technique metabolomics approach to studying intracellular metabolites of HepG2 cells exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin

BackgroundIn vitro cell systems together with omics methods represent promising alternatives to conventional animal models for toxicity testing. Transcriptomic and proteomic approaches have been widely applied in vitro but relatively few studies have used metabolomics. Therefore, the goal of the present study was to develop an untargeted methodology for performing reproducible metabolomics on in vitro systems. The human liver cell line HepG2, and the well-known hepatotoxic and non-genotoxic carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), were used as the in vitro model system and model toxicant, respectively.ResultsThe study focused on the analysis of intracellular metabolites using NMR, LC-MS and GC-MS, with emphasis on the reproducibility and repeatability of the data. State of the art pre-processing and alignment tools and multivariate statistics were used to detect significantly altered levels of metabolites after exposing HepG2 cells to TCDD. Several metabolites identified using databases, literature and LC-nanomate-Orbitrap analysis were affected by the treatment. The observed changes in metabolite levels are discussed in relation to the reported effects of TCDD.ConclusionsUntargeted profiling of the polar and apolar metabolites of in vitro cultured HepG2 cells is a valid approach to studying the effects of TCDD on the cell metabolome. The approach described in this research demonstrates that highly reproducible experiments and correct normalization of the datasets are essential for obtaining reliable results. The effects of TCDD on HepG2 cells reported herein are in agreement with previous studies and serve to validate the procedures used in the present work.

Assessing the Metabolic Competence of Sandwich-Cultured Mouse Primary Hepatocytes

Primary human and rat hepatocyte cultures are well established in vitro systems used in toxicological studies. However, whereas transgenic mouse models provide an opportunity for studying mechanisms of toxicity, mouse primary hepatocyte cultures are less well described. The potential usefulness of a mouse hepatocyte-based in vitro model was assessed in this study by investigating time-dependent competence for xenobiotic metabolism and gene expression profiles. Primary mouse hepatocytes, isolated using two-step collagenase perfusion, were cultured in a collagen sandwich configuration. Gene expression profiles and the activities of various cytochrome P450 (P450) enzymes were determined after 0, 42, and 90 h in culture. Principal component analysis of gene expression profiles shows that replicates per time point are similar. Gene expression levels of most phase I biotransformation enzymes decrease to approximately 69 and 57% of the original levels at 42 and 90 h, respectively, whereas enzyme activities for most of the studied P450s decrease to 59 and 34%. The decrease for phase II gene expression is only to 96 and 92% of the original levels at 42 and 90 h, respectively. Pathway analysis reveals initial effects at the level of proteins, external signaling pathways, and energy production. Later effects are observed for transcription, translation, membranes, and cell cycle-related gene sets. These results indicate that the sandwich-cultured primary mouse hepatocyte system is robust and seems to maintain its metabolic competence better than that of the rat hepatocyte system.

Discrimination for genotoxic and nongenotoxic carcinogens by gene expression profiling in primary mouse hepatocytes improves with exposure time.

Assessing the potential carcinogenicity of chemicals for humans represents an ongoing challenge. Chronic rodent bioassays predict human cancer risk at only limited reliability and are simultaneously expensive and long lasting. In order to seek for alternatives, the ability of a transcriptomics-based primary mouse hepatocyte model to classify carcinogens by their modes of action was evaluated. As it is obvious that exposure will induce a cascade of gene expression modifications, in particular, the influence of exposure time in vitro on discriminating genotoxic (GTX) carcinogens from nongenotoxic (NGTX) carcinogens class discrimination was investigated. Primary mouse hepatocytes from male C57Bl6 mice were treated for 12, 24, 36, and 48 h with two GTX and two NGTX carcinogens. For validation, two additional GTX compounds were studied at 24 and 48 h. Immunostaining of gammaH2AX foci was applied in order to phenotypically verify DNA damage. It confirmed significant induction of DNA damage after treatment with GTX compounds but not with NGTX compounds. Whole-genome gene expression modifications were analyzed by means of Affymetrix microarrays. When using differentially expressed genes from data sets normalized by Robust Multi-array Average, the two classes and various compounds were better separated from each other by hierarchical clustering when increasing the treatment period. Discrimination of GTX and NGTX carcinogens by Prediction Analysis of Microarray improved with time and resulted in correct classification of the validation compounds. The present study shows that gene expression profiling in primary mouse hepatocytes is promising for discriminating GTX from NGTX compounds and that this discrimination improves with increasing treatment period.

Confirmation of quantitative trait loci affecting fatness in chickens.

In this report we describe the analysis of an advanced intercross line (AIL) to confirm the quantitative trait locus (QTL) regions found for fatness traits in a previous study. QTL analysis was performed on chromosomes 1, 3, 4, 15, 18, and 27. The AIL was created by random intercrossing in each generation from generation 2 (G2) onwards until generation 9 (G9) was reached. QTL for abdominal fat weight (AFW) and/or percentage abdominal fat (AF%) on chromosomes 1, 3 and 27 were confirmed in the G9 population. In addition, evidence for QTL for body weight at the age of 5 (BW5) and 7 (BW7) weeks and for the percentage of intramuscular fat (IF%) were found on chromosomes 1, 3, 15, and 27. Significant evidence for QTL was detected on chromosome 1 for BW5 and BW7. Suggestive evidence was found on chromosome 1 for AFW, AF% and IF%, on chromosome 15 for BW5, and on chromosome 27 for AF% and IF%. Furthermore, evidence on the chromosome-wise level was found on chromosome 3 for AFW, AF%, and BW7 and on chromosome 27 for BW5. For chromosomes 4 and 18, test statistics did not exceed the significance threshold.

Alterations in transcript abundance of bovine oocytes recovered at growth and dominance phases of the first follicular wave

BackgroundOocyte developmental competence is highly affected by the phase of ovarian follicular wave. Previous studies have shown that oocytes from subordinate follicles recovered at growth phase (day 3 after estrus) are developmentally more competent than those recovered at dominance phase (day 7 after estrus). However, the molecular mechanisms associated with these differences are not well elucidated. Therefore, the objective of this study was to investigate transcript abundance of bovine oocytes retrieved from small follicles at growth and dominance phases of the first follicular wave and to identify candidate genes related to oocyte developmental competence using cDNA microarray.ResultsComparative gene expression analysis of oocytes from growth and dominance phases and subsequent data analysis using Significant Analysis of Microarray (SAM) revealed a total of 51 differentially regulated genes, including 36 with known function, 6 with unknown function and 9 novel transcripts. Real-time PCR has validated 10 transcripts revealed by microarray analysis and quantified 5 genes in cumulus cells derived from oocytes of both phases. The expression profile of 8 (80%) transcripts (ANAXA2, FL396, S100A10, RPL24, PP, PTTG1, MSX1 and BMP15) was in agreement with microarray data. Transcript abundance of five candidate genes in relation to oocyte developmental competence was validated using Brilliant Cresyl Blue (BCB) staining as an independent model. Furthermore, localization of mRNA and protein product of the candidate gene MSX1 in sections of ovarian follicles at days 0, 1, 3 and 7 of estrous cycle showed a clear fluorescent signal in both oocytes and cumulus cells with higher intensity in the former. Moreover, the protein product was detected in bovine oocytes and early cleavage embryos after fertilization with higher intensity around the nucleus.ConclusionThis study has identified distinct sets of differentially regulated transcripts between bovine oocytes recovered from small follicles at growth and dominance phases of the first follicular wave. The validation with independent model supports our notion that many of the transcripts identified here may represent candidate genes associated with oocyte developmental competence. Further specific functional analysis will provide insights into the exact role of these transcripts in oocyte competence and early embryonic development.

A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo

The lack of accurate in vitro assays for predicting in vivo toxicity of chemicals together with new legislations demanding replacement and reduction of animal testing has triggered the development of alternative methods. This study aimed at developing a transcriptomics-based in vitro prediction assay for in vivo genotoxicity. Transcriptomics changes induced in the human liver cell line HepG2 by 34 compounds after treatment for 12, 24, and 48 h were used for the selection of gene-sets that are capable of discriminating between in vivo genotoxins (GTX) and in vivo nongenotoxins (NGTX). By combining transcriptomics with publicly available results for these chemicals from standard in vitro genotoxicity studies, we developed several prediction models. These models were validated by using an additional set of 28 chemicals. The best prediction was achieved after stratification of chemicals according to results from the Ames bacterial gene mutation assay prior to transcriptomics evaluation after 24h of treatment. A total of 33 genes were selected for discriminating GTX from NGTX for Ames-positive chemicals and 22 for Ames-negative chemicals. Overall, this method resulted in 89% accuracy and 91% specificity, thereby clearly outperforming the standard in vitro test battery. Transcription factor network analysis revealed HNF3a, HNF4a, HNF6, androgen receptor, and SP1 as main factors regulating the expression of classifiers for Ames-positive chemicals. Thus, the classical bacterial gene mutation assay in combination with in vitro transcriptomics in HepG2 is proposed as an upgraded in vitro approach for predicting in vivo genotoxicity of chemicals holding a great promise for reducing animal experimentations on genotoxicity.

Dielectrophoretic behavior of in vitro-derived bovine metaphase II oocytes and zygotes and its relation to in vitro embryonic developmental competence and mRNA expression pattern.

Selecting developmentally competent oocytes and zygotes based on their morphology is more often influenced by personal judgments and lacks universal standards. Therefore, this experiment was conducted to investigate the rate of development and mRNA level of dielectrophoretically separated oocytes and zygotes to validate dielectrophoresis (DEP) as non-invasive option for selection of oocytes and zygotes. In the first experiment, metaphase II oocytes with (PB(+)) and without (PB(-)) first polar body and zygotes were subjected to DEP at 4 MHz and 450 mum electrode distance and classified into fast, very fast, slow, and very slow depending on the time elapsed to reach one of the electrodes in the electric field. Parthenogenetic activation was employed to monitor the embryonic development of dielectrophoretically classified oocytes. The result revealed that at 6 and 7 days of post-activation, the blastocyst rate of very slow dielectrophoretic PB(+) and PB(-) oocytes was significantly (P < 0.05) lower than other groups. Similarly, in zygotes, the blastocyst rate at 7 days post-insemination was higher (P < 0.05) in the very fast dielectrophoretic categories when compared with the slow and very slow categories. In the second experiment, mRNA level was analyzed in the very fast and very slow dielectrophoretic PB(+) oocytes and zygotes respectively using the bovine cDNA microarray. The result showed that 36 and 42 transcripts were differentially regulated between the very fast and very slow dielectrophoretic categories PB(+) oocytes and zygotes respectively. In conclusion, dielectrophoretically separated oocytes and zygotes showed difference in the rate of blastocyst development accompanied by difference in transcriptional abundances.

Gene expression profiling in primary mouse hepatocytes discriminates true from false-positive genotoxic compounds.

Well-established in vitro methods for testing the genotoxic potency of chemicals--such as the Ames/Salmonella test, the mouse lymphoma assay, the micronucleus test and the chromosomal aberration test--show a high false-positive rate for predicting in vivo genotoxicity and carcinogenicity. Thus, there is a need for more reliable in vitro assays. We investigated whether gene expression profiling in metabolically competent primary mouse hepatocytes is capable of discriminating true genotoxic (GTX) compounds from false-positive genotoxic (FP-GTX) compounds. Sandwich-cultured primary hepatocytes from male C57Bl6 mice were treated for 24 and 48 h with five true GTX and five FP-GTX compounds. Whole genome gene expression modifications were analysed by means of Affymetrix mouse genome 430 2.0 microarrays. Filtered genes were used for hierarchical clustering and class prediction methods. Classifiers were generated by prediction analysis of microarray using a leave-one-compound-out method and selecting the genes that were common to the 10 training sets. For the training compounds, all but one were correctly classified. Validation of the classification model with five new compounds resulted in a 100% correct classification at 24 h and 80% at 48 h. The generated classifiers were mostly involved in metabolic and biosynthetic processes, immune responses and apoptosis. Applying genes whose expression change correlates with γH2AX foci, a measure for DNA damage, did not improve the classification. The present study shows that gene expression profiling in primary mouse hepatocytes is capable of discriminating between true GTX and FP-GTX compounds.

Transcriptomic and metabolomic data integration

Many studies now produce parallel data sets from different omics technologies; however, the task of interpreting the acquired data in an integrated fashion is not trivial. This review covers those methods that have been used over the past decade to statistically integrate and interpret metabolomics and transcriptomic data sets. It defines four categories of approaches, correlation-based integration, concatenation-based integration, multivariate-based integration and pathway-based integration, into which all existing statistical methods fit. It also explores the choices in study design for generating samples for analysis by these omics technologies and the impact that these technical decisions have on the subsequent data analysis options.