Project description:The effect of drugs, disease and other perturbations on mRNA levels are studied using gene expression microarrays or RNA-seq, with the goal of understanding molecular effects arising from the perturbation. Previous comparisons of reproducibility across laboratories have been limited in scale and focused on a single model. The use of model systems, such as cultured primary cells or cancer cell lines, assumes that mechanistic insights derived with would have been observed via in vivo studies. We examined the concordance of compound-induced transcriptional changes using data from several sources: rat liver and rat primary hepatocytes (RPH) from Drug Matrix (DM) and open TG-GATEs (TG), primary human hepatocytes (HPH) from TG, and mouse liver / HepG2 results from the Gene Expression Omnibus (GEO) repository. Gene expression changes for treatments were normalized to controls and analyzed with three methods: 1) gene level for 9071 high expression genes in rat liver, 2) gene set analysis (GSA) using canonical pathways and gene ontology sets, 3) weighted gene co-expression network analysis (WGCNA). Co-expression networks performed better than genes or GSA on a quantitative metric when comparing treatment effects within rat liver and rat vs. mouse liver. Genes and modules performed similarly at Connectivity Map-style analyses, where success at identifying similar treatments among a collection of reference profiles is the goal. Comparisons between rat liver and RPH, and those between RPH, HPH and HepG2 cells reveal low concordance for all methods. We investigate differences in the baseline state of cultured cells in the context of drug-induced perturbations in rat liver and highlight the striking similarity between toxicant-exposed cells in vivo and untreated cells in vitro. Gene expression studies in model systems are widely used for understanding the mechanism of drugs and other perturbations in biological systems. Other researchers have examined the reproducibility of microarray studies between laboratories, or comparing microarrays and/or RNA sequencing. However, no large scale studies have compared results from protocols which differ in minor details, or results generated in vivo vs. in vitro culture system thought to serve as useful models. The rat liver is by far the most extensively studied model evaluating effects of drugs and other perturbations, and existing data allowed us to assess the level of concordance between rat liver and rat primary hepatocytes cultured in collagen-coated plates (i.e. âflatâ culture) for hundreds of drugs. We found that the mouse liver serves as a better model of the rat liver than do rat primary hepatocytes, even after allowing for differences due to pharmacokinetics. The low concordance observed between rat liver and rat hepatocytes suggests that validating the utility of âomics data generated on emerging cell culture approaches (e.g. âorgan-on-a-chipâ, 3D-printed tissues) using rat cells and comparison to the rat liver may be necessary in order to gain confidence these approaches substantially improve on traditional culture models of human cells. To identify transcriptional changes in culture, rat primary hepatocytes (RPH) were isolated from three male Sprague Dawley rats. During the isolation and prior to perfusion, a lobe of liver was tied off to serve as the liver in situ reference sample. Cells were isolated and samples from the cell pellet (time zero) and cells cultured for 4, 24 and 48 hours. Three biological replicates were generated for each group (one from each rat). Each biological replicate was analyzed via 3 technical replicates, for a total of 9 array hybridizations per group.

Project description:Chronic liver inflammation precedes the majority of hepatocellular carcinomas (HCC). Here, we explore the connection between chronic inflammation and DNA methylation in the liver at the late precancerous stages of HCC development in Mdr2/Abcb4-knockout (Mdr2-KO) mice, a model of inflammation-mediated HCC. Using methylated DNA immunoprecipitation (MeDIP) followed by hybridization with Agilent CpG Islands (CGIs) microarrays we found specific CGIs in 76 genes which were hypermethylated in the Mdr2-KO liver compared to age-matched controls. Methylation of thirty among these genes was highly specific to the studied HCC model. We revealed that in most tested cases, the observed hypermethylation resulted from an age-dependent decrease of methylation of the specific CGIs in control livers with no decrease in mutant mice. Chronic inflammation did not change global levels of DNA methylation in Mdr2-KO liver, but caused a 2-fold decrease of the global 5-hydroxymethylcytosine level in mutants compared to controls. This decrease could result from a less efficient age-dependent demethylation of specific CpG sites in the liver of Mdr2-KO mutants, as described above. Expression of some tested hypermethylated genes was increased in Mdr2-KO livers compared to controls (28%), others were either similarly expressed (44%), or not expressed in the liver (28%). Liver cell fractionation revealed, that the relative hypermethylation of specific CGIs in Mdr2-KO compared to control livers affected either hepatocyte, or non-hepatocyte, or both fractions. There was only episodic correlation between changes of gene methylation and expression in cell fractions. Conclusion: Chronic liver inflammation causes hypermethylation of specific CGIs, which may affect both hepatocytes and non-hepatocyte liver cells. These changes may serve as markers of an increased regenerative activity and of a precancerous microenvironment in the chronically inflamed liver. Two-condition experiment, Mdr2-KO vs Mdr2-/+ liver tissue from 12m-old male FVB strain mice. Biological replicates: 3 control replicates, 3 knockout replicates.

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Transcriptional profiling of PNPase KO liver hepatocytes

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