Transcriptome profiling of human hepatocytes treated with Aroclor 1254 reveals transcription factor regulatory networks and clusters of regulated genes

Fraunhofer Institute of Toxicology and Experimental Medicine (Fh-ITEM), Center for Drug Research and Medical Biotechnology, Nikolai-Fuchs-Str, 1, 30625 Hannover, Germany.
BMC Genomics (Impact Factor: 3.99). 02/2006; 7(1):217. DOI: 10.1186/1471-2164-7-217
Source: PubMed


Aroclor 1254 is a well-known hepatotoxin and consists of a complex mixture of polychlorinated biphenyls (PCBs), some of which have the ability to activate the aryl hydrocarbon receptor (AhR) and other transcription factors (TFs). Altered transcription factor expression enables activation of promoters of many genes, thereby inducing a regulatory gene network. In the past, computational approaches were not applied to understand the combinatorial interplay of TFs acting in concert after treatment of human hepatocyte cultures with Aroclor 1254. We were particularly interested in interrogating promoters for transcription factor binding sites of regulated genes.
Here, we present a framework for studying a gene regulatory network and the large-scale regulation of transcription on the level of chromatin structure. For that purpose, we employed cDNA and oligomicroarrays to investigate transcript signatures in human hepatocyte cultures treated with Aroclor 1254 and found 910 genes to be regulated, 52 of which code for TFs and 47 of which are involved in cell cycle and apoptosis. We identified regulatory elements proximal to AhR binding sites, and this included recognition sites for the transcription factors ETS, SP1, CREB, EGR, NF-kB, NKXH, and ZBP. Notably, ECAT and TBP binding sites were identified for Aroclor 1254-induced and E2F, MAZ, HOX, and WHZ for Aroclor 1254-repressed genes. We further examined the chromosomal distribution of regulated genes and observed a statistically significant high number of gene pairs within a distance of 200 kb. Genes regulated by Aroclor 1254, are much closer located to each other than genes distributed randomly all over the genome. 37 regulated gene pairs are even found to be directly neighbored. Within these directly neighbored gene pairs, not all genes were bona fide targets for AhR (primary effect). Upon further analyses many were targets for other transcription factors whose expression was regulated by Aroclor 1254 (secondary effect).
We observed coordinate events in transcript regulation upon treatment of human hepatocytes with Aroclor 1254 and identified a regulatory gene network of different TFs acting in concert. We determined molecular rules for transcriptional regulation to explain, in part, the pleiotropic effect seen in animals and humans upon exposure to Aroclor 1254.

Download full-text


Available from: PubMed Central · License: CC BY
  • Source
    • "Moreover, we found that the module 106 (Fig. 4D) identified three candidate genes associated with alcoholism (PDE11A, HCP9 and TTN) and that all of these genes have plausible biological bases for being involved in alcoholism, such as being part of the calcium signalling pathway, regulation of the actin cytoskeleton and focal adhesion. Although PDE11A and TTN did not directly interact with each other in the protein–protein interaction network and the distance between them is 417,650 bp, which is larger than the threshold of colocalised genes used in Susanne Reymann et al. (Reymann and Borlak, 2006) (other modules' ranges are given in Table S12), they still exhibit significant synergistic effects. In agreement with previous studies, this result indicates that synergetic effects of genes located in biochemically distinct circuits are common (Hartman et al., 2001; Wagner et al., 2008). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Detection of the synergetic effects between variants, such as single-nucleotide polymorphisms (SNPs), is crucial for understanding the genetic characters of complex diseases. Here, we proposed a two-step approach to detect differentially inherited SNP modules (synergetic SNP units) from a SNP network. First, SNP-SNP interactions are identified based on prior biological knowledge, such as their adjacency on the chromosome or degree of relatedness between the functional relationships of their genes. These interactions form SNP networks. Second, disease-risk SNP modules (or sub-networks) are prioritised by their differentially inherited properties in IBD (Identity by Descent) profiles of affected and unaffected sibpairs. The search process is driven by the disease information and follows the structure of a SNP network. Simulation studies have indicated that this approach achieves high accuracy and a low false-positive rate in the identification of known disease-susceptible SNPs. Applying this method to an alcoholism dataset, we found that flexible patterns of susceptible SNP combinations do play a role in complex diseases, and some known genes were detected through these risk SNP modules. One example is GRM7, a known alcoholism gene successfully detected by a SNP module comprised of two SNPs, but neither of the two SNPs was significantly associated with the disease in single-locus analysis. These identified genes are also enriched in some pathways associated with alcoholism, including the calcium signalling pathway, axon guidance and neuroactive ligand-receptor interaction. The integration of network biology and genetic analysis provides putative functional bridges between genetic variants and candidate genes or pathways, thereby providing new insight into the aetiology of complex diseases.
    Full-text · Article · Sep 2011 · Gene
  • Source
    • "However, the Hif1 and Foxn1 TFBS showed enrichment within the 1893 regions that showed significant AHR binding and did not co-occur with the AHR. In an in silico analysis of promoter regions from genes showing differential expression in primary human hepatocytes following exposure to Aroclor 1254, the TFBS for Nrf1 (V$NRF1) and Npas2 (V$HIFF) co-occurred with the AHR TFBS (Reymann and Borlak, 2006). In our study, the AHR and Nrf1 module was identified. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The aryl hydrocarbon receptor (AHR) agonist 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) alters differentiation of B cells and suppresses antibody production. A combination of whole-genome, microarray-based chromatin immunoprecipitation (ChIP-on-chip), and time course gene expression microarray analysis was performed on the mouse B-cell line CH12.LX following exposure to lipopolysaccharide (LPS) or LPS and TCDD to identify the primary and downstream transcriptional elements of B-cell differentiation that are altered by the AHR. ChIP-on-chip analysis identified 1893 regions with a significant increase in AHR binding with TCDD treatment. Transcription factor binding site analysis on the ChIP-on-chip data showed enrichment in AHR response elements. Other transcription factors showed significant coenrichment with AHR response elements. When ChIP-on-chip regions were compared with gene expression changes at the early time points, 78 genes were identified as potential direct targets of the AHR. AHR binding and expression changes were confirmed for a subset of genes in primary mouse B cells. Network analysis examining connections between the 78 potential AHR target genes and three transcription factors known to regulate B-cell differentiation indicated multiple paths for potential regulation by the AHR. Enrichment analysis on the differentially expressed genes at each time point evaluated the downstream impact of AHR-regulated gene expression changes on B-cell-related processes. AHR-mediated impairment of B-cell differentiation occurred at multiple nodes of the B-cell differentiation network and potentially through multiple mechanisms including direct cis-acting effects on key regulators of B-cell differentiation, indirect regulation of B-cell differentiation-related pathways, and transcriptional coregulation of target genes by AHR and other transcription factors.
    Full-text · Article · Dec 2010 · Toxicological Sciences
  • Source
    • "As suggested by others (Beekman et al., 2006; McMillian et al., 2004; Reymann and Borlak, 2006; Van Delft et al., 2005), a high chemical concentration causing limited cytotoxicity, if at all, has to be investigated in order to evaluate toxic effects together with an active transcriptional activity. In the present study, we show that an 8 mM phenobarbital (PB) concentration caused reproducible effects, characterized by more than one thousand constantly modulated genes, in spite of the use of widely different experimental conditions. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The use of in vitro human liver cell models is an attractive approach in toxicogenomic studies designed to analyze gene expression changes induced by a toxic chemical. However, in such studies, reliability, reproducibility and interlaboratory concordance of microarrays, as well as the choice of the most suitable cell model, remain a matter of debate. This work was aimed at evaluating the robustness of microarray technologies and the suitability of the highly differentiated human HepaRG cell line in the investigation of gene expression changes induced by a toxic compound in human liver. The influence of various experimental conditions including cell cultures grown at different test sites, different generations of microarrays, RNA analysis platforms and softwares, was tested on gene expression profiles induced by a 20h treatment with an 8mM concentration of phenobarbital as the toxic compound. As many as 1099 genes (p-value<0.01 and 1.5-fold-change), representing 74% and 30% of the signature genes detected with Agilent 22 and 44K pangenomic microarrays, respectively, were shown to be modulated in common in six independently performed experiments. The most modulated genes included both those known to be regulated by phenobarbital, such as cytochromes P450 and membrane transporters, and those involved in oxidative stress, inflammation and apoptosis, typifying a toxic insult. These data provide strong support for the use of a toxicogenomic approach for the in vitro prediction of chemical toxicity, and for the choice of human HepaRG cells as a promising model system for human hepatotoxicity testing.
    Preview · Article · Dec 2008 · Toxicology in Vitro
Show more