One-month-old C3H male mice (Harlan Sprague-Dawley, San Diego, CA) were fed DDC (0.1% diethyl-1, 4-dihydro-2,4,6-trimethyl-3,5-pyridinedicarboxylate (Aldrich, St Louis, MD) for 10 weeks to induce MDB formation in vivo
. The mice were then withdrawn from the drug for 1 month (n-4
) and refed DDC with or without betaine (2% in the drinking water) for 7 days. The control mice n=4 were fed control diet (Yuan et al., 1996
). Mice fed DDC for 10 weeks and then withdrawn from DDC for 1 month (n=4) served as withdrawn controls. All mice were treated in a humane manner as approved by the Animal Care Committee at Harbor-UCLA Laboratory BioMedical Research Institute according to the Guidelines of the National Academy of Science.
Liver tissue was fixed in 10% buffered zinc formalin. Liver sections were double stained using a mouse monoclonal antibody to CK-8 (Fitzgerald, RDI, Concord, MA) and a rabbit polyclonal antibody to ubiquitin (Dako, Carpinteria, CA) (). Double staining with antibodies to FAT10 (UBD) and PCNA was also done. Quantitation of MDB positive cells, FAT10 positive cells and PCNA positive nuclei were performed using a Nikon morphometric system and a Nikon 400 fluorescent microscope. Texas-red and FITC-conjugated second antibodies were used. DAPI was the nuclear stain.
The isolation of nuclei was carried out according to the method of Umlauf et al
. (Umlauf et al., 2004
). Liver tissue, frozen in isopentane immersed in liquid nitrogen was homogenized in a Dounce homogenizer with 10 strokes in 1 ml of buffer-I. The homogenates were centrifuged for 10 min at 6000×g. The Pellets were then resuspended in buffer-II, placed on ice for 10 min and then centrifuged 20 min at 9000g on a sucrose cushion (buffer III). All buffers used contained protease inhibitors: 10 mM benzamidine, 0.7 μg/ml leupeptin, 50 μg/ml soy bean trypsin inhibitor, 0.2 μg/ml aprotinin, 2 μg/ml antipain, 0.7 μg/ml pepstatin, 0.5 mM PMSF, and 0.5 mM AEBSF (Calbiochem, La Jolla, CA), sodium butyrate 5 mM and DTT 1 mM. Protein concentrations were measured using the Bradford method (Bradford, 1976
), and bovine serum albumin was the protein standard.
The protocol for Histone isolation was done using the protocol of Shechter et al
. (Shechter et al., 2007
). Briefly, isolated nuclei were mixed with 0.4 N H2
and incubated on a rotator for 30 min. at 4°C. Samples were spun in a microcentrifuge at 16,000 g, 10 min. Dissolved histones in the supernatant were then precipitated with 33% TCA. After an acetone wash the histones were dissolved in an appropriate buffer and further analyzed.
Western Blot Analysis
Proteins (50 μg) from liquid nitrogen frozen stored livers and nuclear and histone extracts were separated by SDS-PAGE gels and transferred to a PVDF membrane (Bio-Rad, Hercules, CA) for 1 h in 25 mM Tris-HCl (pH 8.3), 192 mM glycine and 20% methanol. The membranes were stained using primary antibodies to antigens (). Appropriate species polyclonal and monoclonal HRP-conjugated antibodies were used as the secondary antibodies. The membranes were subjected to chemiluminescence detection using luminal, according to the manufacturer’s instructions (Amersham Pharmacia Biotech, Piscataway, NJ). The antibodies used were: Ubiquitin, PCNA (DAKO, Carpinteria, CA), BHMT, AMD1 (Abcam, Cambridge, MA), FAT10 (BioMol, Plymouth, PA), Cytokeratin 8 (RDI, Concord, MA), AHCY (ABR, Golden, CO).
Quantitative Real-time RT-PCR Assay
Total liver RNAs were extracted with Trizol Plus RNA Purification Kit (Invitrogen, Carlsbad, CA) as described previously (Li et al., 2008
). The sequences of PCR primers are:
Liver tissue from three mouse of each of the 4 treatment groups was subjected to microarray analysis. Total liver RNA is extracted with Ultraspec™ RNAs Isolation Systemic (Biotecz Laboratories, Houston, TX) and are cleaned up with Rneasy columns (Qiagen, Valencia, CA). Five micrograms of total RNA was used for preparing biotin-labeled cRNA. Labeled and fragmented cRNA is subsequently hybridized to Mouse Genome 430 2.0 Array (Affymetrix, Santa Clara, CA). Labeling, hybridization, image scanning and initial data analysis are performed by the Microarray Core at Los Angeles Biomedical Research Institute.
Sample preparation and loading
Equal amounts of RNA (5 μg) from each sample were used for Affymetrix GeneChip analysis. RNA was converted to cDNA using GeneChip® One-Cycle cDNA Synthesis Kit (Affymetrix) and then to biotinylated cRNA using GeneChip® IVT Labeling Kit (Affymetrix). The quality of labeled RNA was confirmed with the Affymetrix Test 3 Array. The biotinylated cRNA from all samples was hybridized to Affymetrix Mouse 430 2.0 GeneChip arrays.
Hybridization and staining
Hybridization cocktail was prepared, which includes controls at the fragmented cRNA. The samples were hybridized in the array at 45°C for 17 h using GeneChip Hybridization Oven 640. Immediately following hybridization, the array underwent an automated washing and staining protocol (R-Phycoerythin Streptavidin conjugated, Molecular Probes) on the GeneChip Fluidics Station 400. The arrays were then scanned with a GeneChip Scanner 3000 (Affymetrix).
Microarray data analysis
Data preparation, analysis, and integration were performed using Affymetrix’s GeneChip Operating Software (GCOS). The software was used to perform image processing, evaluation of data quality, normalization, transformation, and filtering, so that data was ready for further analysis. Wilcoxon’s rank test was used in comparison analysis to derive biologically significant results from the raw probe cell intensities on expression arrays. For comparison analysis, each probe set on the experiment array was compared with its counterpart on the control array to calculate the change in P- value that was used to generate the difference call of increase (I; P < 0.04), marginal increase (MI; P < 0.04 to P < 0.06), decrease (D; P> 0.997), marginal decrease (MD; P> 0.992 to P > 0.997), or no change (NC: P > 0.06 to P < 0.997). Comparison analysis was used to generate a signal log ratio for each probe prior to experimental array to the corresponding probe pair on the control array. This strategy cancels out differences resulting from different probe finding coefficients. Signal log ratio was computed by using a one-step Tukey’s biweight method by taking a mean of the log ratio of probe pair intensities across the two arrays.
Once the absolute and comparison data files were created in GCOS, genes were identified with signal intensity differences using BULLFROG v12.3 TG (Lockhart and Lockhart) and GeneSpring (Silicon Genetics). In the BULLFROG analysis, the filtering criteria used to find genes unique to DDC 7 days was the following: a change call of increase/marginal increase or decrease/marginal decrease, fold change > 1.7 and a present call in at least one of the arrays. In GeneSpring the probes were first normalized using “Per Gene: Normalize to median”. Next, transcripts were determined to be differentially expressed based on the following criteria: a Change Call of Increase, Marginal Increase, Decrease, or Marginal Decrease with a Change P value < 0.006 or > 0.994, a Signal Log Ratio < -0.08 or > 0.8, a Present Call for the probe set in either or both experimental conditions, and a minimum signal intensity of 50 of a probe in either or both of the experimental files.
After generating a list of differentially expressed genes, downstream analysis was performed. The filtered transcripts were clustered in GeneSpring using SOM and K-means and GeneTree to find similar patterns of gene expression. The lists of transcripts were also uploaded into GenMapp (Gene Micro Array Pathway Profiler, Gladstone Institutes University of California at San Francisco). GenMapp clusters the transcripts based on biological function.
The data illustrated were obtained by using the KEGG web site (http://www.genome.jp/kegg/pathway.htm1
) and blasting the list of total changed genes issued from our experiment for analysis. The website calculates the number of up-regulated and down-regulated genes for each pathway shown in the KEGG graph. To determine the present gene change in each pathway, the number of changed genes present in each pathway was divided by the total number of genes in the same pathway.
The same calculation was performed in the ABI panther (http://www.pantherdb.org/genes
) website to illustrate the pie chart. To determine the percent gene change in each pathway, the number of genes present in each pathway was divided by the total number of changed genes.