Y.C.M. Staal

Time Series Analysis of Benzo[A]Pyrene-Induced Transcriptome Changes Suggests That a Network of Transcription Factors Regulates the Effects on Functional Gene Sets

Chemical carcinogens may cause a multitude of effects inside cells, thereby affecting transcript levels of genes by direct activation of transcription factors (TF) or indirectly through the formation of DNA damage. As the temporal profiles of these responses may be profoundly different, examining time-dependent changes may provide new insights in TF networks related to cellular responses to chemical carcinogens. Therefore, we investigated in human hepatoma cells gene expression changes caused by benzo[a]pyrene at 12 time points after exposure, in relation to DNA adduct and cell cycle. Temporal profiles for functional gene sets demonstrate both early and late effects in up- and downregulation of relevant gene sets involved in cell cycle, apoptosis, DNA repair, and metabolism of amino acids and lipids. Many significant transcription regulation networks appeared to be around TF that are proto-oncogenes or tumor suppressor genes. The time series analysis tool Short Time-series Expression Miner (STEM) was used to identify time-dependent correlation of pathways, gene sets, TF networks, and biological parameters. Most correlations are with DNA adduct levels, which is an early response, and less with the later responses on G1 and S phase cells. The majority of the modulated genes in the Reactome pathways can be regulated by several of these TF, e.g., 73% by nuclear factor-kappa B and 34-42% by c-MYC, SRF, AP1, and E2F1. All these TF can also regulate one or more of the others. Our data indicate that a complex network of a few TF is responsible for the majority of the transcriptional changes induced by BaP. This network hardly changes over time, despite that the transcriptional profiles clearly alter, suggesting that also other regulatory mechanisms are involved.

A Lyophilized Red Grape Pomace Containing Proanthocyanidin-Rich Dietary Fiber Induces Genetic and Metabolic Alterations in Colon Mucosa of Female C57BL/6J Mice

Diet plays a decisive role in promoting or preventing colon cancer. However, the specific effects of some nutrients remain unclear. The capacity of fruit and vegetables to prevent cancer has been associated with their fiber and antioxidant composition. We investigated whether consumption of a lyophilized red grape pomace containing proanthocyanidin-rich dietary fiber (grape antioxidant dietary fiber, GADF) by female C57BL/6J mice would affect the serum metabolic profile or colon mucosa gene expression using NMR techniques and DNA microarray, respectively. The mice were randomly assigned to 2 groups that for 2 wk consumed a standard rodent diet and were gavaged with 100 mg/kg body weight GADF suspended in water or an equivalent volume of plain tap water (10 mL/kg body weight). The amount of fiber supplemented was calculated to equal the current recommended daily levels of fiber consumption for humans. The inclusion of dietary GADF induced alterations in the expression of tumor suppressor genes and proto-oncogenes as well as the modulation of genes from pathways, including lipid biosynthesis, energy metabolism, cell cycle, and apoptosis. Overexpression of enzymes pertaining to the xenobiotic detoxifying system and endogenous antioxidant cell defenses was also observed. In summary, the genetic and metabolic profiles induced by GADF were consistent with the preventive effects of fiber and polyphenols. On the basis of these observations, we propose that GADF may contribute to reducing the risk of colon cancer.

Interlaboratory and Interplatform Comparison of Microarray Gene Expression Analysis of HepG2 Cells Exposed to Benzo(a)pyrene.

Microarray technology is being used increasingly to study gene expression of biological systems on a large scale. Both interlaboratory and interplatform differences are known to contribute to variability in microarray data. In this study we have investigated data from different platforms and laboratories on the transcriptomic profile of HepG2 cells exposed to benzo(a)pyrene (BaP). RNA samples generated in two different laboratories were analyzed using both Agilent oligonucleotide microarrays and Cancer Research UK (CR-UK) cDNA microarrays. Comparability of the expression profiles was assessed at various levels including correlation and overlap between the data, clustering of the data and affected biological processes. Overlap and correlation occurred, but it was not possible to deduce whether choice of platform or interlaboratory differences contributed more to the data variation. Principal component analysis (PCA) and hierarchical clustering of the expression profiles indicated that the data were most clearly defined by duration of exposure to BaP, suggesting that laboratory and platform variability does not mask the biological effects. Real-time quantitative PCR was used to validate the two array platforms and indicated that false negatives, rather than false positives, are obtained with both systems. All together these results suggest that data from similar biological experiments analyzed on different microarray platforms can be combined to give a more complete transcriptomic profile. Each platform gives a slight variation in the BaP-gene expression response and, although it cannot be stated which is more correct, combining the two data sets is more informative than considering them individually.

Interactions between polycyclic aromatic hydrocarbons in binary mixtures: Effects on gene expression and DNA adduct formation in precision-cut rat liver slices

Although exposure to polycyclic aromatic hydrocarbons (PAHs) occurs mostly through mixtures, hazard and risk assessment are mostly based on the effects caused by individual compounds. The objective of the current study was to investigate whether interactions between PAHs occur, focusing on gene expression (as measured by cDNA microarrays) and DNA adduct formation. The effects of benzo[a]pyrene or dibenzo[a,h]anthracene (DB[a,h]A) alone and in binary mixtures with another PAH (DB[a,h]A, benzo[b]fluoranthene, fluoranthene or dibenzo[a,l]pyrene) were investigated using precision-cut rat liver slices. All compounds significantly modulated the expression of several genes, but overlap between genes affected by the mixture and by the individual compounds was relatively small. All mixtures showed an antagonistic response on total gene expression profiles. Moreover, at the level of individual genes, mostly antagonism was evident, with additivity and synergism observed for only a few genes. As far as DNA adduct formation is concerned, the binary mixtures generally caused antagonism. The effects in liver slices suggest a lower carcinogenic potency of PAH mixtures than estimated based on additivity of individual compounds.

Application of four dyes in gene expression analyses by microarrays.

BackgroundDNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes.ResultsFollowing tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation.ConclusionIn conclusion, the four dyes can be used simultaneously for gene expression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressed genes with comparable effects on gene expression.