An integrated functional genomic study of acute phenobarbital exposure in the rat

Abstract

Background: Non-genotoxic carcinogens are notoriously difficult to identify as they do not damage DNA directly and have diverse modes of action, necessitating long term in vivo studies. The early effects of the classic rodent non-genotoxic hepatocarcinogen phenobarbital have been investigated in the Fisher rat using a combination of metabolomics and transcriptomics, to investige early stage mechanistic changes that are predictive of longer term pathology.

Results: Liver and blood plasma were profiled across 14 days, and multivariate statistics used to identify perturbed pathways. Both metabolomics and transcriptomics detected changes in the liver which were dose dependent, even after one day of exposure. Integration of the two datasets associated perturbations with specific pathways. Hepatic glycogen was decreased due to a decrease in synthesis, and plasma triglycerides were decreased due to an increase in fatty acid uptake by the liver. Hepatic succinate was increased and this was associated with increased heme biosynthesis. Glutathione synthesis was also increased, presumably in response to oxidative stress. Liquid Chromatography Mass Spectrometry demonstrated a remodeling of lipid species, possibly resulting from proliferation of the smooth endoplasmic reticulum.

Conclusions: The data fusion of metabolomic and transcriptomic changes proved to be a highly sensitive approach for monitoring early stage changes in altered hepatic metabolism, oxidative stress and cytochrome P450 induction simultaneously. This approach is particularly useful in interpreting changes in metabolites such as succinate which are hubs of metabolism.

Figure 1

Liver histopathology. Liver histology. Upper panel: light microscopy image of hematoxylin and eosin stained liver tissue from control (A) and PB treated (B) animals. Livers from PB treated animals show centrilobular hypertrophy, compression of the periportal areas and eosinophilc appearance. Lower panel: electron microscopy images of control (C) and PB treated livers (D, E & F). PB treated livers showed dispersion of organelles and proliferation of the smooth endoplasmic reticulum.

Figure 2

PLS modeling of metabolomic data. PLS plots correlating metabolic profiles with dose of PB at day 14 using ¹H-NMR (A), GC-MS analysis of the aqueous extract (B), and GC-MS analysis of the lipid extract (C). In addition to the use of Q² values, models were validated to prevent over fitting by leaving samples out of the model building stage and then predicting their dose of PB (D) (mean ± standard deviation of 5 iterations) and also by using the validate function in SIMCA-P+ with 200 iterations (E). In this approach the actual model is compared with models formed where the Y value (in this case dose) is randomly permuted to produce models where there should be no correlation between the X-block and Y-block matrices. As demonstrated in panel E, the decreases in R² and Q² as the dose is randomly permuted is indicative of a robust model. PLS analysis of MAS ¹H-NMR data separated the control and low dose from the mid and high dose groups (F). The corresponding loadings column plot (G i) and assigned spectra (G ii) showed that exposure to PB increased lipids and decreased sugars. The ratio of total lipid to total carbohydrate was increased in the mid and high dose groups compared to the control group (H). Plot show average ± standard deviation (n = 5) with significant changes as determined by ANOVA with Dunnett's post test for multiple comparisons labelled ** (p < 0.01). Key: Control (filled square) 50 ppm (open circle) 500 ppm (filled triangle) 1000 ppm (open circle).

Figure 3

Plasma lipoprotein profile. PLS plots correlating metabolic profiles with dose of PB at day 14 using ¹H-NMR spectroscopy of blood plasma (A). Key: Control (filled square), 50 ppm (open circle), 500 ppm (filled triangle), 1000 ppm (open square). Overlaid ¹H-NMR spectra from the region containing the terminal methyl group of fatty acids in blood plasma (B). A change in the shape of the peak, with an increase in the proportion of lower chemical shift, higher density lipoprotein with increasing dose of PB is clearly detected. This is characteristic of an increase in high density lipoprotein particles relative to low density lipoprotein particles.

Figure 4

Hierarchical clustering of transcriptomic data. Hierarchical clustering using Pearson correlation coefficients revealed different temporal patterns of gene expression changes due to exposure to phenobarbital. Some genes were transiently upregulated at early time points (A &B), whereas others showed a sustained decrease (C) or increase (D) in expression.

Figure 5

Integration of metabolomic and transcriptomic data using pathway mapping. Overlaid ¹H-NMR spectra from day 14 samples showing a dose dependent decrease in glycogen. A similar response is seen at all other time points (A). The glycogen synthesis pathway demonstrating the correlation between transcriptional and metabolic changes. Hexokinase D, which is involved in control of the rate of glycogen synthesis, is decreased indicating that the decrease in glycogen is due to decreased synthesis (B). Glutathione synthesis pathway. Due to the extraction procedure, all glutathione detected is oxidized [38]. The increase in glutathione at days 1, 3 and 7 is likely to be due to an increase in glutamate cysteine ligase expression (C). The key to the gene expression data is given in (D).

Figure 6

Integration of metabolomic and transcriptomic data using PLS. Partial Least Squares (PLS) plots modeling changes in gene expression associated with hepatic succinate at all time points (A) and CH₂ of plasma lipids at days 7 and 14 (B), both measured by ¹H-NMR spectroscopy. The increase in succinate detected with increasing dose of PB correlates with an increase in 5-aminolevulinate synthase (ALAS) expression and the decrease in plasma lipids detected with increasing dose of PB correlates with an increase in lipoprotein lipase (LPL) expression. Control (filled sqaure), 50 ppm (open circle), 500 ppm (filled triangle), 1000 ppm (open square).

Figure 7

Lipidomic analysis of the liver tissue. Overlaying typical direct infusion ESI-MS spectra from the control, 50 ppm, 500 ppm and 1000 ppm groups at day 14 illustrates some of the changes occurring in the intact lipids. The 16:0 containing GpIns species are increased by exposure to PB and GpEtn species containing 18:0 in combination with a HUFA are decreased by exposure to PB. The GpEtn species are observed as adducts with an unknown species of mass 50.