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Comparative analysis of gene expression profiles of acute hepatic failure and that of liver regeneration in rat
Gene 528 (2013) 59–66
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Review
Comparative analysis of gene expression profiles of acute hepatic failure and that of liver regeneration in rat Cunshuan Xu a,b,⁎, Weiming Zhao a, Yunpeng Hao a,b, Cuifang Chang a,b, Jinyu Fan b a b
College of Life Sciences, Henan Normal University, Xinxiang 453007, Henan Province, China Key Laboratory for Cell Differentiation Regulation, HNP-STM, Xinxiang 453007, Henan Province, China
a r t i c l e
i n f o
Article history: Accepted 2 July 2013 Available online 1 August 2013 Keywords: Acute hepatic failure (AHF) Liver regeneration (LR) Gene expression profiles Physiological activity
a b s t r a c t To explore the relevance of rat liver regeneration (LR) to acute hepatic failure (AHF), Rat Genome 230 2.0 Array was used to detect their gene expression profiles in this study, and the reliability of the detection results was confirmed by real-time-PCR. 1012 genes were found to be significantly changed in AHF occurrence and 948 genes in LR. Hierarchical clustering analysis showed that physiological activities of AHF and those of LR had no time correlation. Hierarchical clustering analysis (which is performed to group genes based on the similarity of expression patterns) showed that physiological activities of AHF and those of LR had no time correlation. K-means clustering analysis (which is used to check the difference in the relevant predictor variables between different groups is significant or not) demonstrated that gene expression trend of C1 group (genes relate to categories of stimulus–response and cell apoptosis, etc.) in AHF and in LR was extremely similar, that those of their C2 group (categories of regulation of homeostasis and hormone stimulation, etc.) were contrary, and that those of their C3 (material and energy metabolism and oxidation reduction, etc.), C4 (Cell cycle-related genes) and C5 (cell proliferation-related genes) groups were also similar with the gene expression changes of LR more abundant. GO classifications and functional clustering analysis (which was used to statistics the numbers or composition of proteins or genes at a function level) revealed that cellular processes including immune response, inflammatory reaction, cell migration and adhesion, etc. were increased both in AHF and in LR, whereas material and energy metabolism were decreased. Of them, stimulus response, inflammatory reaction and regulation of apoptosis, etc. were stronger in AHF occurrence than in LR, but ion homeostasis, hormonal response, regulation of cell division and proliferation, etc. were weaker in AHF occurrence. Gene expression changes and physiological activities of AHF and those of LR not only have similarities but also differences. © 2013 Elsevier B.V. All rights reserved.
Contents 1. 2.
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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Preparation of rat acute hepatic failure model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Preparation of rat regenerating liver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Rat genome 230 2.0 microarray detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5. Identification of genes related to acute hepatic failure and liver regeneration . . . . . . . . . . . . . . . 2.6. Gene ontology analysis of genes related to acute hepatic failure and genes related to liver regeneration . . . 2.7. Quantitative RT-PCR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Comparative analysis of the detection results of real-time polymerase chain reaction and that of microarray . 3.2. Comparative analysis of gene expression profiles of rat acute hepatic failure and that of rat liver regeneration
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Abbreviations: A, absent; AHF, acute hepatic failure; CCl4, carbon tetrachloride; HGF, hepatocyte growth factor; LR, liver regeneration; M, marginal; NC, normal control; P, present; PH, partial hepatectomy; RT-PCR, real-time polymerase chain reaction; SD, Sprague–Dawley; SO, sham-operated. ⁎ Corresponding author at: College of Life Science, Henan Normal University, No. 46, Construction East Road, Xinxiang 453007, Henan Province, China. Tel.: +86 0373 3326001; fax: +86 0373 3326524. E-mail addresses: [email protected], [email protected] (C. Xu). 0378-1119/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.gene.2013.07.023
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3.3. Comparison of expression patterns of AHF-related genes with those of LR-related genes 3.4. Expression patterns and function clustering of AHF-related genes and LR-related genes . 4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction Liver is the largest digestive gland in human body, and has many functions, such as, detoxification and metabolism. Of numerous hepatic diseases, acute hepatic failure (AHF) is more harmful, and AHF remains an extremely poor prognosis and still results in high mortality. Therefore, better treatment is urgently needed (Park et al., 2012). Ichida (2003) and Ambrosino et al. (2003) both demonstrated that promoting regeneration of hepatic cells and/or blocking their apoptosis is beneficial to the treatment and the prognosis of AHF. Kaido and Imamura (2001) found that hepatocyte growth factor (HGF) could not only promote the proliferation of hepatic cells, but also improve their detoxification and anti-injury abilities. Gao et al. (2009) reported that human augmenter of liver regeneration (rhALR) could cure carbon tetrachloride (CCl4)-induced mice AHF. Yu et al. (2009) held that transplanted hepatocytes could promote the initiation of liver regeneration during AHF. Tomiya et al. (2008) pointed out that impaired regenerative capacity of patients with AHF might be attributable, in part, to a disruption of communication of growth-associated factors. All the studies above demonstrated that liver regeneration (LR) is closely related to AHF. This study will further compare analysis of the gene expression profiles of rat LR and rat AHF at the gene transcription level and may put forward some new guidance for the treatment of acute hepatic failure. Usually, AHF occurrence was divided into injury phase with necrosis and apoptosis of mass hepatic cells (3–6 h after CCL4 treatment), progressing phase with severe inflammation response (12–24 h after CCL4 treatment) and recovery phase with cell proliferation and differentiation (48–72 h after CCL4 treatment), and 21 kinds of cellular processes including stimulation and inflammation responses, metabolism, cell proliferation, differentiation and apoptosis were found to be involved in AHF occurrence (Cheng and Tian, 2010; Felipo and Butterworth, 2002; Mookerjee et al., 2007). LR triggered by 2/3 hepatectomy (PH) was also divided into priming phase with cell activation (0–6 h after PH), progressing phase with cell proliferation (12–72 h after PH) and terminal phase with reconstruction of tissue structure (120–168 h after PH) (Fausto et al., 2006; Taub, 2004; C.S. Xu et al., 2005; Z. Xu et al., 2005). Therefore, the comparative studies of their gene expression profiles will help to advance the research on their similarities and differences at the transcription level, and elucidate the molecular mechanism of AHF occurrence. Hence, our group studied the gene expression profiles of rat AHF based on functional genomic analysis of rat LR, and analyzed the relationships between gene transcription profiles of rat AHF and those of rat LR.
2. Materials and methods 2.1. Animals Twelve-week-old adult healthy Sprague–Dawley (SD) rats, each weighing 250–320 g, were supplied by the Experimental Animal Center of Henan Normal University, and were housed in standard laboratory conditions (temperature 22 ± 1 °C, relative humidity 50–60%, and 12:12 h light–dark cycle with lights at 8:00–20:00). All the rats were fed with standard rodent chow diet with free access to distilled water.
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The whole handling procedure went in accordance with the current Animal Protection Law of China. 2.2. Preparation of rat acute hepatic failure model Carbon tetrachloride (CCl4) is widely used to generate an experimental model mimicking acute liver failure caused by toxic substances (Jin et al., 2009). 28 male rats were randomly divided into 7 groups with 4 rats in each including 6 rat acute hepatic failure (AHF) group with 24 rats, and one control group with 4 rats. Carbon tetrachloride (CCl4) was diluted 2:3 in sesame oil under the sterile conditions. The rats in AHF were fed with a single dose of 4 ml/kg diluted CCl4, and 4 livers were taken for use at each of the following time points: 3, 6, 12, 24, 48 and 72 h after CCl4 treatment. Livers of control group were taken at 0 h. The livers were immediately washed three times in 0.01 mol/L phosphate-buffered saline (PBS) at 4 °C after being taken. For each liver, approximately 100–200 mg liver tissues were taken from the middle parts of its right lobe on ice and stored at −80 °C for use. 2.3. Preparation of rat regenerating liver 76 rats were randomly divided into 19 groups with 4 rats in each including 9 partial hepatectomy (PH) groups, 9 sham-operated (SO) groups and one normal control (NC) group. PH groups were subjected to 2/3 PH, as described by Higgins and Anderson (1931). SO group received the same procedure as for the PH group without liver removal. Four rats were anesthetized and sacrificed at each of the following time points: 0, 2, 6, 12, 24, 30, 36, 72, 120 and 168 h after PH, respectively, and their livers were instantly removed and stored at − 80°C for use. 2.4. Rat genome 230 2.0 microarray detection Total RNA was extracted according to the manual of Trizol reagent (Invitrogen Corporation, Carlsbad, California, USA) and purified following the RNeasy mini protocol (Qiagen, Inc, Valencia, CA, USA). The quality of total RNA was assessed by optical density measurement at 260/280 nm and agarose electrophoresis (180 V, 0.5 h). It was regarded as qualified sample, when 28S RNA to 18S RNA is equal to 2:1. T7-oligo dT(24) (Keck Foundation, New Haven, CT) SuperScript II RT (Invitrogen Corporation, Carlsbad, CA) and 5 μg of total RNA were used to synthesize the first strand of cDNA. The second strand was synthesized using the Affymetrix cDNA single-stranded cDNA synthesis kit. The 12 μl purified cDNA and the reagents in the GeneChip In Vitro Transcript Labeling Kit (ENZO Biochemical, New York, USA) were used to synthesize biotinlabeled cRNA. The labeled cRNA was purified using the RNeasy Mini Kit columns (Qiagen, Valencia, CA). 15 μl cRNA (1 μg/μl) was incubated with 6 μl 5 × fragmentation buffer and 9 μl RNase free water for 35 min at 94 °C, and digested into 35–200 bp cRNA fragments. The prehybridized Rat Genome 230 2.0 Microarray was put into a hybridization buffer, and the hybridization was at 45 °C in a hybridization oven (Affymetrix) at 60 rpm for 16 h. The hybridized arrays were washed by wash buffer, and stained in GeneChip® Fluidics Station 450 (Affymetrix Inc., Santa Clara, CA, USA). Then the arrays were scanned and imaged with a
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Fig. 1. mRNA expression of four selected genes measured by microarrays and RT-PCR. Solid line presented the results of RT-PCR and dotted line that of Rat Genome 230 2.0 Array.
GeneChip® Scanner 3000 (Affymetrix Inc., Santa Clara, CA, USA) (Xu et al., 2008a, 2008b). 2.5. Identification of genes related to acute hepatic failure and liver regeneration Those images showing gene expression abundance were converted into signal values, signal detection values (P (present), A (absent), M (marginal)) and experiment/control values (Ri) using Affymetrix GCOS 2.0. The data of each array were initially normalized by scaling all signals to a target intensity of 200. When P value is b 0.05, it means that the gene is present (P), when b0.065, means marginal (M), and when N0.065, means marked absent (A). On the other hand, the normalized signal values in model group of LC or PH group to that in control were used to calculate the relative value, that is, ratio value of gene expression abundance. When ratio value is ≥3, it means that gene expression was significantly up-regulated, when ≤0.33, significantly down-regulated, and when 0.33–2.99, biologically non-significant. To minimize the technical errors from microarray analysis, each sample was tested at least three times using Rat Genome 230 2.0 microarray, and the average value was
400
considered as a reliable value. The genes were expressed significantly at least once during CCL4-inducedAHF and were considered as AHFrelated genes, and the genes which have been significantly changed during liver regeneration (LR) with significant difference (0.01 ≤ P b 0.05) or extremely significant difference (P ≤ 0.01) between PH and SO, as LR-related genes. 2.6. Gene ontology analysis of genes related to acute hepatic failure and genes related to liver regeneration In order to compare expression patterns of AHF-related genes with those of LR-related genes, we employed k-means clustering to classify the genes involved in AHF or in LR (Fig. 5). EASE (Expressing Analysis Systematic Explorer) is a network platform for functional enrichment analysis characterized by providing some statistical tests to determine whether the GO categories are over-represented or not. Firstly, the genes in every cluster were mapped to their corresponding unique genes, and GO analysis assigned each gene to a class of biological function. Then EASE analysis was conducted to identify GO categories in every cluster that are over-represented according to EASE
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Rcovery time(h) after Acute hepatic failure(AFH)/ partial hepatectomy(PH) Fig. 2. Number of expressed genes related to acute hepatic failure and that of liver regeneration. □ Number of up-regulated genes related to AHF, related to AHF, Number of up-regulated genes related to LR and Number of down- regulated genes related to LR.
Number of down-regulated genes
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3. Results 3.1. Comparative analysis of the detection results of real-time polymerase chain reaction and that of microarray
Fig. 3. The distribution of genes associated with acute hepatic failure (AHF) and those associated with liver regeneration (LR). 552 LR-specific genes were composed of 362 up-regulated genes and 190 down-regulated, and 626 AHF-specific genes, 413 up-regulated genes and 213 down-regulated.
score (a modified Fisher's exact test), with the Bonferroni multiple testing correction (Hosack et al., 2003; Huang et al., 2009; Out et al., 2007). The GO categories with EASE scores of b 0.05 are considered to be significantly over-represented, and the GO categories with EASE scores of b0.01 are considered to be extremely significantly over-represented. 2.7. Quantitative RT-PCR Four genes, related to inflammation and stimulus responses, drug metabolism, gene transcription, proliferation and apoptosis of cells and some transcription factors, were selected for RT-PCR assays to verify the chip data. The primers were designed with Primer Express 2.0 software according to mRNA sequences of target genes A2M, SPP1, CYP1A1 and TRIM24 (GenBank number: NM_012488, NM_012881, NM_012540 and NM_001044266) and synthesized by Shanghai Generay Biotech Co., Ltd. The gene-specific primers were as follows: forward primer 5′-CGAACATCCGTAAACCCAAAGTC-3′ and reverse primer 5′-GCTG AGTCCACCACCACCAAGTC-3′ for A2M, forward primer 5′-TGATGA CGACG- ACGATGACGATGG-3′ and 5′-ACGCTGGGCAACTGGGATGAC CTT-3′ reverse primer for SPP1, forward primer 5′-AGGACAGGAGG CTGGACGAGA-3′, and reverse primer 5′-ATGGTGAATGGGACAAAGGAT-3′ for CYP1A1, forward primer 5′-CAGTGGGAGGGTCTTACAA TC-3′ and reverse primer 5′-CTGGCCAGGGTCTACACTTG-3′ for TRIM24. Total RNA (2 μg) was reverse-transcripted using random primers and reverse transcription kit (Promega). First-strand cDNA samples were subjected to quantitative PCR amplification by using SYBR® Green I on the Rotor-Gene Rotor-Gene 3000A (Corbett Robotics, Brisbane, Australia), and the reaction condition was 95 °C 2 min, 95 °C 15 s, 60 °C 15 s, 72 °C 30 s, 40 cycles. Every sample was analyzed in triplicate. Standard curves were generated from five repeated ten-fold serial dilutions of cDNA, and the copy numbers of target genes in every milliliter of the sample were calculated according to their corresponding standard curves (Wang and Xu, 2010).
To confirm the results of the microarray analysis, RT-PCR assays were used to detect the expression changes of the genes including A2M and TRIM24 (these two genes are both related to AHF and LR), and SPP1 and CYP1A1 (they are only related to AHF), and at 3, 6, 12, 24, 48 and 72 h after CCl4 treatment and that in regenerating livers at 0, 2, 6, 12, 24, 30, 36, 72, 120 and 168 h after PH. Even though the abundance relative expression values of the genes detected by above two methods were not all the same, expression trends were generally consistent, suggesting that the array detection results were reliable (Fig. 1). 3.2. Comparative analysis of gene expression profiles of rat acute hepatic failure and that of rat liver regeneration Rat Genome 230 2.0 array was used to detected the gene expression profiles of acute hepatic failure (AHF), showing that a total of 1012 genes, including 631 up-regulated and 381 down-regulated genes, has significantly changed during AHF occurrence. Among them, 207genes were significantly changed at 3 h after CCl4 treatment, 438 genes at 6 h, 470 genes at 12 h, 640 genes at 24 h, 427 genes at 48 h, and 269 genes at 72 h (Fig. 2). The gene expression profiles of rat liver regeneration (LR) were also detected as above, and it was found that 948 genes, composed of 611 up-regulated and 337 down-regulated genes, were significantly expressed during LR. In detail, 185 genes were significantly expressed at 2 h after PH, 314 genes at 6 h, 384 genes at 12 h, 297 genes at 24 h, 369 genes at 30 h, 253 genes at 36 h, 405 genes at 72 h, 92 genes at 120 h, and 81 genes at 168 h (Fig. 2). It was obvious that the up-regulated genes kept more than the down-regulated in the two processes, and that the AHF-associated genes were expressed mainly at the progressing phase (12–48 h) of AHF occurrence, while LR-associated genes mainly at the progressing phase (6–72 h) after PH. Moreover, 626 genes were the AHF-specific genes, 552 genes were the LR-specific and 396 genes were the common genes (Fig. 3). To compare AHF with LR on the whole, this study carried out H-clustering analysis. The results showed that 3, 6, 12 h and 24 h of AHF occurrence were clustered, so were 48 and 72 h of AHF occurrence, 6 and 12 h, 2 and 168 h, 72 and 120 h, 24, 30 and 36 h during LR (Fig. 4). It was clear that some time points of AHF and those of LR were always highly correlated, though their gene expression profiles were different on the whole. Therefore, the correlation between their gene expression profiles needed a further exploration (Fig. 4). 3.3. Comparison of expression patterns of AHF-related genes with those of LR-related genes In order to explore the similarities and the differences between the expression patterns of AHF-related genes and those of LR-related genes, we looked up the expression changes of 1022 AHF-related genes during
Fig. 4. A cladogram about expression time correlation of acute liver failure (AHF)-related genes and liver regeneration (LR)-related genes. Symbols in red represent the expression time points of AHF-related genes and those in blue the expression time points of LR-related genes.
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Fig. 5. Global comparison of gene expression patterns of AHF-related genes with those of LR-related genes. A. H-cluster; B. Gene expression patterns of AHF (left panel) and LR (right panel).
LR and those of 948 LR-related genes in the occurrence of AHF, then a total of 1574 genes were obtained with expression values at 14 time points (3, 6, 12, 24, 48 and 72 h after CCl4 treatment and 2, 6, 12, 24, 30, 36, 72, 120, and 168 h of LR). Subsequently, 1574 genes above were categorized into 6 clusters by k-means (Fig. 5A). Of them, Cluster 1 contained 251 genes which were significantly changed in expression, peaking at 6 h during AHF occurrence while up-regulated slightly at the priming phase after PH. Cluster 2 contained 145 genes which were significantly down-regulated with the expression peak at 3 h during AHF occurrence, but were up-regulated with an expression peak at 2 h during LR. Cluster 3 involved 531 genes, which were decreased in the two processes, peaking at 24 h during AHF occurrence and at 12 and 30 h during LR. Cluster 4 contained 263 genes, which were remarkably up-regulated at the recovery phase, peaking at 48 h during AHF occurrence, but upregulated at the progressing phase, peaking at 24 and 36 h during LR. 101 genes were embodied in cluster 5, and they displayed increased
expression with a peak at 24 h during AHF occurrence, and so did they with peaks at 6 h, 30 h, and 72 h during LR (Fig. 5B). 3.4. Expression patterns and function clustering of AHF-related genes and LR-related genes According to gene ontology database (GO), AHF-related genes and LR-related genes were involved in 23 kinds of physiological activities including stimulus, inflammation and immune response, material and energy metabolism, cell proliferation, growth, differentiation, development, apoptosis, migration and adhesion. This study performed expressing analysis systematic explorer (EASE) analysis on the genes sets of clusters 1–5 in Fig. 5, and the over-represented GO categories were selected from each cluster according to the EASE scores (Table 1). In each category, the number of genes precedes the modified EASE score (P value). These categories with EASE scores of b0.05 represented classes of genes in which
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C. Xu et al. / Gene 528 (2013) 59–66 Table 1 (continued)
Table 1 Expression patterns and function clustering of AHF-related genes and LR-related genes in rat. Cluster enriched biological process
No. of genes
P-value
C1 Response to organic substance Response to endogenous stimulus Response to organic cyclic substance Response to hormone stimulus Response to abiotic stimulus Response to oxidative stress Response to cAMP Response to steroid hormone stimulus Response to inorganic substance Regulation of apoptosis Regulation of programmed cell death Regulation of cell death Transcription C2 Ion homeostasis Response to organic substance Response to hormone stimulus C3 Amine catabolic process Carboxylic acid biosynthetic process Carboxylic acid catabolic process Cellular amino acid derivative metabolic process Cofactor metabolic process Energy derivation by Oxidation of organic compounds Energy reserve metabolic process Fatty acid metabolic process Glucose metabolic process Lipid biosynthetic process Lipid catabolic process Organic acid biosynthetic process Organic acid catabolic process Oxidation reduction Response to drug Response to endogenous stimulus Response to extracellular stimulus Response to organic substance Response to steroid hormone stimulus Steroid metabolic process Vitamin metabolic process Xenobiotic metabolic process C4 Cell cycle Cell cycle phase Cell cycle process Cell division Chromosome organization DNA metabolic process DNA repair DNA replication DNA-dependent DNA replication M phase M phase of mitotic cell cycle Microtubule-based process Mitotic cell cycle Nuclear division Organelle fission Regulation of cell cycle Response to DNA damage stimulus C5 Biological adhesion Cell adhesion Cell migration Cell motion Chemotaxis Defense response Defense response to bacterium Immune response Inflammatory response Leukocyte activation Localization of cell Positive regulation of immune system process Positive regulation of response to stimulus Regulation of cell proliferation Regulation of inflammatory response Regulation of leukocyte activation Response to bacterium Response to hormone stimulus Response to molecule of bacterial origin
48 34 19 29 24 16 10 19 18 30 30 30 31 11 22 14 17 27 22 25 24 14 9 33 19 35 16 27 22 81 35 45 33 63 28 34 18 9 61 44 53 28 26 49 24 33 17 37 24 22 35 23 23 22 28 32 32 26 31 22 52 13 47 34 24 26 29 21 43 14 20 28 32 21
2.40E-11 1.50E-09 3.30E-08 8.40E-08 5.70E-07 8.10E-07 1.60E-06 3.90E-06 5.20E-06 7.80E-06 1.00E-05 1.10E-05 3.30E-06 2.60E-03 4.00E-05 4.60E-04 3.30E-11 1.10E-13 2.90E-13 7.10E-11 1.60E-08 1.10E-05 1.70E-05 2.10E-16 2.90E-06 8.90E-13 6.50E-06 1.10E-13 2.90E-13 6.00E-32 6.30E-11 1.90E-09 1.50E-10 2.00E-10 7.20E-08 7.70E-19 4.00E-11 2.00E-07 8.30E-41 2.30E-35 1.30E-37 3.10E-22 3.00E-11 3.50E-33 3.30E-15 3.70E-31 1.60E-20 1.90E-31 6.60E-21 1.10E-12 6.20E-25 5.60E-20 2.10E-19 1.00E-10 1.00E-15 1.40E-06 1.40E-06 1.60E-08 4.40E-07 1.60E-15 1.00E-21 5.00E-06 3.20E-17 1.40E-16 7.60E-09 1.50E-06 1.20E-11 2.80E-06 8.10E-08 1.30E-07 3.80E-08 7.70E-12 1.00E-05 1.10E-10
Cluster enriched biological process Response to organic substance Response to wounding
No. of genes
P-value
58 50
7.40E-10 5.20E-19
P-value represents EASE score (a modified Fisher's exact test).
individual members occurred more often than would be expected by a random distribution of genes. Obviously, cluster 1 (C1) was enriched with the genes in categories of stimulus response and cell apoptosis, etc. The genes in cluster 2 (C2) were functionally classified into the categories of regulation of homeostasis and hormone stimulation, etc. A higher proportion of genes in cluster 3 (C3) were associated with material and energy metabolism and oxidation reduction, etc. Cell cycle and cell proliferation-related genes were predominant in cluster 4 (C4). Cluster 5 (C5) was full of some genes regulating cell proliferation and genes related to immunity, inflammation and trauma responses, cell and migration, etc. (Table 1). 4. Discussion In the past, acute hepatic failure (AHF) and liver regeneration (LR) have aroused great attention because of their close association with stimulus and inflammation responses, rapid proliferation and growth of cells. Consequently, many researchers attempted to find out the similarities and differences between their cellular processes, in order to elucidate the mechanism of AHF (Li et al., 2010; Xu et al., 2007). In this study, Rat Genome 230 2.0 array was used to detect gene expression profiles of liver tissues from the carbon tetrachloride (CCl4)-treated rats and regenerating livers at different time points after partial hepatectomy (PH), and it was found that 1022 genes were associated with AHF occurrence and 948 genes with LR. Among them, 396 genes were the common genes. GO analysis showed that stimulus, immune and inflammatory responses, material metabolism and transport, cell proliferation, growth, differentiation, development, migration and adhesion were involved both in AHF occurrence and in LR, but their degrees of correlation with AHF and with LR were different (Lockhart et al., 2003; Rosen et al., 2008; C.S. Xu et al., 2005; Z. Xu et al., 2005). Previous studies have proven that hepatic cells sensed the decrease in tissue oxygenation, then activated hypoxia-inducible signaling pathways, and promoted liver cell survival (Plock et al., 2007). In this study of 51 stimulus-related genes, blood bilirubin-regulating gene ABCC3 (Chang et al., 2004), CYP11A1 involved in stress response, and insulin-induced protein homology INSIG1, were up-regulated in AHF occurrence. Early growth factor gene EGR1, eukaryotic translation initiation factor gene EIF2B3, insulin-like growth factor binding protein gene IGFBP1, and transforming growth factor gene TGFB3 were up-regulated in AHF occurrence, but showed insignificant changes in LR. Therefore, t the regulation mechanisms of stimulus response were indicated to be different in the two processes. In addition, among 24 genes related to regulation of apoptosis, glutamate cysteine ligase modifier subunit GCLM, nuclear protein gene NUPR1, were up-regulated in AHF occurrence, while down- regulated in LR. The above-mentioned genes were rich in cluster 1 (Table 1), and significantly up-regulate in AHF occurrence, but downregulated or showing insignificant changes in LR. It was suggested that stimulus response, cell apoptosis, in AHF occurrence were stronger than in LR, meaning that AHF occurrence was regulated by the apoptosisrelated genes above, which was consistent with the research results by Singhal et al. (2009). This study found that 33 genes were involved in regulating ion and hormone homeostases. Of them, calcium release channel gene RYR3, sodium channel alpha subunit SCN8A, one member of solute carrier family SLC34A, tachykinin gene TAC1, lysyl oxidase LOX, transforming growth factor beta receptor TGFBR2, and interleukin receptor gene IL1R1 were down-regulated in AHF occurrence, but up-regulated in LR. The 33
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genes above were predominant in cluster 2 (Table 1), implying that calcium, sodium and hormone homeostases differed between AHF occurrence and LR, when subjected to different external stimuli. Xu et al. (2008a, 2008b) and Guo and Xu (2008) hold that carbohydrates, lipid, amino acid and nucleic acid metabolisms were enhanced, and were the basis of material and energy metabolisms during LR. According to this study, cluster 3 was enriched with genes related to metabolism, oxidation reduction and drug response (Table 1). They were down-regulated at 6–48 h of the two processes with more genes in LR than in AHF occurrence, and the expression abundance of these genes were greater, which meant that impaired liver function significantly affected material metabolism both in AHF occurrence and in LR (Jiang et al., 2007). In detail, amine catabolism-related gene DMGDH, kynurenine 3-hydroxylase genes KMO and KYNU, glutathione transferase gene LOC681913, oxidation reduction-related alcohol dehydrogenase genes ADH1 and ADHFE1, and aldehyde-keto reductase family member gene AKR1B7 were down-regulated both in AHF and in LR, which suggested that the level of oxidation reduction in the two processes was decreased. In addition, lipid metabolism-related genes, including sterols isomerase gene EBP, enoyl acylating coenzyme A reductive enzyme gene GPSN2, 3-hydroxy-3-methylglutaryl-Coenzyme A synthase gene HMGCS1, glycometabolism-related genes including glucokinase regulatory protein gene GCKR and hepatocyte nuclear factor gene ONECUT1, and amino acid metabolism-related genes including picolinate carboxylase gene ACMSD and apolipoprotein gene APOA2 were down-regulated at many time points of AHF occurrence, while showing insignificant changes in LR, which indicated that carbohydrates, lipid and amino acid metabolisms in LR were stronger than in AHF occurrence (Schneeweiss et al., 1993; Xu and Chang, 2008). Studies showed that both AHF and LR included cell proliferation and damage repair. Yang et al. (2009) found that LR would occur at a relative late time point when expression of cell cycle protein cyclin D1 was decreased. Hence, it was significant to explore the similarities and differences of their cell proliferations (Xu et al., 2007). In this study, 126 genes associated with cell cycle and cell proliferation were harbored in cluster 4 (Table 1). Among them, cancer-induced gene BRCA2, replication initiation complex subunit ORC6L, cell cyclin genes CCNA2 and CCNE2, cyclin-dependent kinase CDC2A, began to be up-regulated from 24 h with a peak at 48 h during AHF occurrence, while peaked at 24 and 72 h during LR, which agreed with the finding that hepatocyte proliferation occurred at 24 h, and the proliferation peak of non-parenchymal liver cells occurred late during LR (Koniaris et al., 2003; Palmes and Spiegel, 2004). As a whole, cell division machinery worked actively in cell proliferation and growth of AHF and LR. In addition, DNA repair gene BLM, MCM10 involved in DNA replication micro-chromosomal repair protein, and inhibition apoptosis TBC1 family member gene TBC1D12 were up-regulated in LR, while down-regulated or showing insignificant changes in AHF occurrence. Based on expression differences of these genes in above two events, it was inferred that DNA damage repair mechanism was poor in AHF occurrence, causing a high error rate of DNA replication, and that the regulation of cell proliferation in LR was relatively perfect, which was consistent with the previous studies (Xu et al., 2007). Perhaps it is the real reason that causes recovery of liver injury slow in AHF, but fast in LR. It is generally believed that cell adhesion and migration are closely related to infiltration and metastasis of immune and inflammatory cells in AHF occurrence, meanwhile, they were important to structure–function rebuilding in LR (Li et al., 2007). This study found that 159 genes related to immune and inflammation responses, cell adhesion and migration had a high proportion in cluster 5 (Table 1). Of them, laminin gene LAMC1, former calcium adhesion protein gene FAT1, and adhesion molecule CD24 were up-regulated in AHF occurrence, but displayed nonsignificant changes in LR, which meant that cell adhesion and migration in AHF occurrence were stronger than in LR. Mookerjee et al. (2007) found that inflammatory cell could produce inflammatory cytokines and chemokines in AHF occurrence, and
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reactive oxygen species and other substances produced by these factors were detrimental to cell survival and would increase the risk of AHF occurrence (Jansen et al., 2009). Thus, the differences between inflammatory response in liver cells to external stimulation in AHF occurrence and that in LR deserved a further study (Taub et al., 1999; Wang et al., 2009). This study demonstrated that of 144 inflammation-related genes, tumor necrosis factor genes TNF and TNF14, interleukin gene IL1B promoting the secretion of cytokines, RT1-DA and RT1-M3 promoting antigen presentation showed insignificant changes in AHF occurrence, but were up-regulated in LR, which indicated that as liver injury went, inflammatory response in AHF became weaker than in LR. Hence, it was speculated that apoptosis and necrosis of liver cells at the late phase of AHF might be caused by their decreased resistance against various stimulus. 5. Conclusion In short, this study analyzed the gene expression profiles of AHF and that of LR, and carried out functional enrichment analysis to analyze the physiological activities uncovered by the profiles. It is concluded that gene expression changes and physiological activities of AHF and those of LR not only have similarities but also differences, and we will confirm the results of this study using gene addition, knock-out, and RNAi in future. Conflict of interest There is no competing financial interests exist. Acknowledgments This work was supported by the National Basic Research 973 Preresearch Program of China, No. 2012CB722304. Meanwhile, we were grateful to Xueliang Wang for his revising the English manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2013.07.023. References Ambrosino, G., et al., 2003. Hepatocyte transplantation in the treatment of acute liver failure: microencapsulated hepatocytes versus hepatocytes attached to an autologous biomatrix. Cell Transplant. 12, 43–49. Chang, T.H., Hakamada, K., Toyoki, Y., Tsuchida, S., Sasaki, M., 2004. Expression of MRP2 and MRP3 during liver regeneration after 90% partial hepatectomy in rats. Transplantation 77, 22–27. Cheng, W.T., Tian, D.Y., 2010. Effects and mechanism of endotoxemia on carbohydrate metabolism in D-GalN-reduced acute hepatic failure rats. Chin. J. Integr. Tradit. West. Med. 20, 38–40. Fausto, N., Campbell, J.S., Riehle, K.J., 2006. Liver regeneration. Hepatology 43, 45–53. Felipo, V., Butterworth, R.F., 2002. Mitochondrial dysfunction in acute hyperammonemia. Neurochem. Int. 40, 487–491. Gao, C.F., Zhou, F., Wang, H., Huang, Y.F., Ji, Q., Chen, J., 2009. Genetic recombinant expression and characterization of human augmenter of liver regeneration. Dig. Dis. Sci. 54, 530–537. Guo, G.B., Xu, C.S., 2008. Expression profiles of the organic acid metabolism-associated genes during rat liver regeneration. Amino Acids 34, 597–604. Higgins, G.M., Anderson, R.M., 1931. Experimental pathology of the liver: restoration of the liver of the white rat following partial surgical removal. Arch. Pathol. Lab. Med. 12, 186–202. Hosack, D.A., Dennis Jr., G., Sherman, B.T., Lane, H.C., Lempicki, R.A., 2003. Identifying biological themes within lists of genes with EASE. Genome Biol. 4, 70. Huang, D.W., Sherman, B.T., Lempicki, R.A., 2009. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57. Ichida, T., 2003. Artificial liver support system for fulminant hepatic failure as bridgehouse to living donor liver transplantation. Intern. Med. 42, 967–970. Jansen, P.A.M., et al., 2009. Expression of the vanin gene family in normal and inflamed human skin: induction by proinflammatory cytokines. J. Invest. Dermatol. 129, 2167–2174. Jiang, J.T., Xu, N., Zhang, X.Y., Wu, C.P., 2007. Lipids changes in liver cancer. J. Zhejiang Univ. Sci. B 8, 398–409.
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Jin, S.Z., Meng, X.W., Han, M.Z., Sun, X., Sun, L.Y., Liu, B.R., 2009. Stromal cell derived factor-1 enhances bone marrow mononuclear cell migration in mice with acute liver failure. World J. Gastroenterol. 7, 2657–2664. Kaido, T., Imamura, M., 2001. Hepatocyte growth factor: clinical implications in hepatobiliary pancreatic surgery. J. Hepatobiliary Pancreat. Surg. 8, 65. Koniaris, L.G., McKillop, I.H., Schwartz, S.I., Zimmers, T.A., 2003. Liver regeneration. J. Am. Coll. Surg. 197, 634–659. Li, H.L., Chen, X.G., Zhang, F.C., Ma, J., Xu, C.S., 2007. Expression patterns of the cell junction-associated genes during rat liver regeneration. J. Genet. Genomics 34, 892–908. Li, T., Wan, B., Huang, J., Zhang, X., 2010. Comparison of gene expression in hepatocellular carcinoma, liver development, and liver regeneration. Mol. Genet. Genomics 283, 485–492. Lockhart, A.C., Tirona, R.G., Kim, R.B., 2003. Pharmacogenetics of ATP-binding cassette transporters in cancer and chemotherapy. Mol. Cancer Ther. 2, 685–698. Mookerjee, R.P., et al., 2007. Inflammation is an important determinant of levels of the endogenous nitric oxide synthase inhibitor asymmetric dimethylarginine (ADMA) in acute liver failure. Liver Transpl. 13, 400–405. Out, H.H., et al., 2007. Restoration of liver mass after injury requires proliferative and not embryonic transcriptional patterns. J. Biol. Chem. 282, 11197–11204. Palmes, D., Spiegel, H.U., 2004. Animal models of liver regeneration. Biomaterials 25, 1601–1611. Park, J.H., et al., 2012. Protective effect of melittin on inflammation and apoptosis in acute liver failure. Apoptosis 17, 61–69. Plock, J., et al., 2007. Activation of non-ischemic, hypoxia-inducible signalling pathways up-regulate cytoprotective genes in the murine liver. J. Hepatol. 47, 538–545. Rosen, M.B., et al., 2008. Toxicogenomic dissection of the perfluorooctanoic acid transcript profile in mouse liver: evidence for the involvement of nuclear receptors PPAR alpha and CAR. Toxicol. Sci. 103, 46–56. Schneeweiss, B., et al., 1993. Energy metabolism in acute hepatic failure. Gastroenterology 105, 1515–1521. Singhal, S., Jain, S., Kohaar, I., Singla, M., Gondal, R., Kar, P., 2009. Apoptotic mechanisms in fulminant hepatic failure: potential therapeutic target. Appl. Immunohistochem. Mol. Morphol. 17, 282–285.
Taub, R., 2004. Liver regeneration: from myth to mechanism. Nat. Rev. Mol. Cell Biol. 5, 836–847. Taub, R., Greenbaum, L.E., Peng, Y., 1999. Transcriptional regulatory signals define cytokinedependent and -independent pathways in liver regeneration. Semin. Liver Dis. 19, 117–127. Tomiya, T., Omata, M., Imamura, H., Fujiwara, K., 2008. Impaired liver regeneration in acute liver failure: the significance of cross-communication of growth associated factors in liver regeneration. Hepatol. Res. 38, 29–33. Wang, G.P., Xu, C.S., 2010. Reference gene selection for real-time RT-PCR in eight kinds of rat regenerating hepatic cells. Mol. Biotechnol. 46, 49–57. Wang, W.B., Fan, J.M., Zhang, X.L., Xu, J., Yao, W., 2009. Serial expression analysis of liver regeneration-related genes in rat regenerating liver. Mol. Biotechnol. 43, 221–231. Xu, C.S., Chang, C.F., 2008. Expression profiles of the genes associated with metabolism and transport of amino acids and their derivatives in rat liver regeneration. Amino Acids 34, 91–102. Xu, C.S., et al., 2005a. Expressed genes in regenerating rat liver after partial hepatectomy. World J. Gastroenterol. 11, 2932–2940. Xu, Z., Chen, L., Leung, L., Yen, T.S., Lee, C., Chan, J.Y., 2005b. Liver-specific inactivation of the Nrf1 gene in adult mouse leads to nonalcoholic steatohepatitis and hepatic neoplasia. Proc. Natl. Acad. Sci. U. S. A. 102, 4120–4125. Xu, C.S., Zhang, S.B., Chen, X.G., Rahman, S., 2007. Correlation analysis of liver tumor-associated genes with liver regeneration. World J. Gastroenterol. 13, 3323–3332. Xu, C.S., Lin, F., Qin, S.W., 2008a. Relevance between lipid metabolism-associated genes and rat liver regeneration. Hepatol. Res. 38, 825–837. Xu, C.S., Zhang, S.B., Yang, Z.L., Cui, S.N., Zhang, M., 2008b. The expression changes of genes associated with protein metabolism, folding, transport, localization and assembly during rat liver regeneration. Fen Zi Xi Bao Sheng Wu Xue Bao 41, 107–119. Yang, R.K., Miki, K., He, X., Killeen, M.E., Fink, M.P., 2009. Prolonged treatment with Nacetylcysteine delays liver recovery from acetaminophen hepatotoxicity. Crit. Care 13, 55. Yu, C.H., Chen, H.L., Chen, Y.H., Chang, M.F., Chien, C.S., Chang, M.H., 2009. Impaired hepatocyte regeneration in acute severe hepatic injury enhances effective repopulation by transplanted hepatocytes. Cell Transplant. 18, 1081–1092.
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Review
Comparative analysis of gene expression profiles of acute hepatic failure and that of liver regeneration in rat Cunshuan Xu a,b,⁎, Weiming Zhao a, Yunpeng Hao a,b, Cuifang Chang a,b, Jinyu Fan b a b
College of Life Sciences, Henan Normal University, Xinxiang 453007, Henan Province, China Key Laboratory for Cell Differentiation Regulation, HNP-STM, Xinxiang 453007, Henan Province, China
a r t i c l e
i n f o
Article history: Accepted 2 July 2013 Available online 1 August 2013 Keywords: Acute hepatic failure (AHF) Liver regeneration (LR) Gene expression profiles Physiological activity
a b s t r a c t To explore the relevance of rat liver regeneration (LR) to acute hepatic failure (AHF), Rat Genome 230 2.0 Array was used to detect their gene expression profiles in this study, and the reliability of the detection results was confirmed by real-time-PCR. 1012 genes were found to be significantly changed in AHF occurrence and 948 genes in LR. Hierarchical clustering analysis showed that physiological activities of AHF and those of LR had no time correlation. Hierarchical clustering analysis (which is performed to group genes based on the similarity of expression patterns) showed that physiological activities of AHF and those of LR had no time correlation. K-means clustering analysis (which is used to check the difference in the relevant predictor variables between different groups is significant or not) demonstrated that gene expression trend of C1 group (genes relate to categories of stimulus–response and cell apoptosis, etc.) in AHF and in LR was extremely similar, that those of their C2 group (categories of regulation of homeostasis and hormone stimulation, etc.) were contrary, and that those of their C3 (material and energy metabolism and oxidation reduction, etc.), C4 (Cell cycle-related genes) and C5 (cell proliferation-related genes) groups were also similar with the gene expression changes of LR more abundant. GO classifications and functional clustering analysis (which was used to statistics the numbers or composition of proteins or genes at a function level) revealed that cellular processes including immune response, inflammatory reaction, cell migration and adhesion, etc. were increased both in AHF and in LR, whereas material and energy metabolism were decreased. Of them, stimulus response, inflammatory reaction and regulation of apoptosis, etc. were stronger in AHF occurrence than in LR, but ion homeostasis, hormonal response, regulation of cell division and proliferation, etc. were weaker in AHF occurrence. Gene expression changes and physiological activities of AHF and those of LR not only have similarities but also differences. © 2013 Elsevier B.V. All rights reserved.
Contents 1. 2.
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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Preparation of rat acute hepatic failure model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Preparation of rat regenerating liver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Rat genome 230 2.0 microarray detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5. Identification of genes related to acute hepatic failure and liver regeneration . . . . . . . . . . . . . . . 2.6. Gene ontology analysis of genes related to acute hepatic failure and genes related to liver regeneration . . . 2.7. Quantitative RT-PCR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Comparative analysis of the detection results of real-time polymerase chain reaction and that of microarray . 3.2. Comparative analysis of gene expression profiles of rat acute hepatic failure and that of rat liver regeneration
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Abbreviations: A, absent; AHF, acute hepatic failure; CCl4, carbon tetrachloride; HGF, hepatocyte growth factor; LR, liver regeneration; M, marginal; NC, normal control; P, present; PH, partial hepatectomy; RT-PCR, real-time polymerase chain reaction; SD, Sprague–Dawley; SO, sham-operated. ⁎ Corresponding author at: College of Life Science, Henan Normal University, No. 46, Construction East Road, Xinxiang 453007, Henan Province, China. Tel.: +86 0373 3326001; fax: +86 0373 3326524. E-mail addresses: [email protected], [email protected] (C. Xu). 0378-1119/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.gene.2013.07.023
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3.3. Comparison of expression patterns of AHF-related genes with those of LR-related genes 3.4. Expression patterns and function clustering of AHF-related genes and LR-related genes . 4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction Liver is the largest digestive gland in human body, and has many functions, such as, detoxification and metabolism. Of numerous hepatic diseases, acute hepatic failure (AHF) is more harmful, and AHF remains an extremely poor prognosis and still results in high mortality. Therefore, better treatment is urgently needed (Park et al., 2012). Ichida (2003) and Ambrosino et al. (2003) both demonstrated that promoting regeneration of hepatic cells and/or blocking their apoptosis is beneficial to the treatment and the prognosis of AHF. Kaido and Imamura (2001) found that hepatocyte growth factor (HGF) could not only promote the proliferation of hepatic cells, but also improve their detoxification and anti-injury abilities. Gao et al. (2009) reported that human augmenter of liver regeneration (rhALR) could cure carbon tetrachloride (CCl4)-induced mice AHF. Yu et al. (2009) held that transplanted hepatocytes could promote the initiation of liver regeneration during AHF. Tomiya et al. (2008) pointed out that impaired regenerative capacity of patients with AHF might be attributable, in part, to a disruption of communication of growth-associated factors. All the studies above demonstrated that liver regeneration (LR) is closely related to AHF. This study will further compare analysis of the gene expression profiles of rat LR and rat AHF at the gene transcription level and may put forward some new guidance for the treatment of acute hepatic failure. Usually, AHF occurrence was divided into injury phase with necrosis and apoptosis of mass hepatic cells (3–6 h after CCL4 treatment), progressing phase with severe inflammation response (12–24 h after CCL4 treatment) and recovery phase with cell proliferation and differentiation (48–72 h after CCL4 treatment), and 21 kinds of cellular processes including stimulation and inflammation responses, metabolism, cell proliferation, differentiation and apoptosis were found to be involved in AHF occurrence (Cheng and Tian, 2010; Felipo and Butterworth, 2002; Mookerjee et al., 2007). LR triggered by 2/3 hepatectomy (PH) was also divided into priming phase with cell activation (0–6 h after PH), progressing phase with cell proliferation (12–72 h after PH) and terminal phase with reconstruction of tissue structure (120–168 h after PH) (Fausto et al., 2006; Taub, 2004; C.S. Xu et al., 2005; Z. Xu et al., 2005). Therefore, the comparative studies of their gene expression profiles will help to advance the research on their similarities and differences at the transcription level, and elucidate the molecular mechanism of AHF occurrence. Hence, our group studied the gene expression profiles of rat AHF based on functional genomic analysis of rat LR, and analyzed the relationships between gene transcription profiles of rat AHF and those of rat LR.
2. Materials and methods 2.1. Animals Twelve-week-old adult healthy Sprague–Dawley (SD) rats, each weighing 250–320 g, were supplied by the Experimental Animal Center of Henan Normal University, and were housed in standard laboratory conditions (temperature 22 ± 1 °C, relative humidity 50–60%, and 12:12 h light–dark cycle with lights at 8:00–20:00). All the rats were fed with standard rodent chow diet with free access to distilled water.
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The whole handling procedure went in accordance with the current Animal Protection Law of China. 2.2. Preparation of rat acute hepatic failure model Carbon tetrachloride (CCl4) is widely used to generate an experimental model mimicking acute liver failure caused by toxic substances (Jin et al., 2009). 28 male rats were randomly divided into 7 groups with 4 rats in each including 6 rat acute hepatic failure (AHF) group with 24 rats, and one control group with 4 rats. Carbon tetrachloride (CCl4) was diluted 2:3 in sesame oil under the sterile conditions. The rats in AHF were fed with a single dose of 4 ml/kg diluted CCl4, and 4 livers were taken for use at each of the following time points: 3, 6, 12, 24, 48 and 72 h after CCl4 treatment. Livers of control group were taken at 0 h. The livers were immediately washed three times in 0.01 mol/L phosphate-buffered saline (PBS) at 4 °C after being taken. For each liver, approximately 100–200 mg liver tissues were taken from the middle parts of its right lobe on ice and stored at −80 °C for use. 2.3. Preparation of rat regenerating liver 76 rats were randomly divided into 19 groups with 4 rats in each including 9 partial hepatectomy (PH) groups, 9 sham-operated (SO) groups and one normal control (NC) group. PH groups were subjected to 2/3 PH, as described by Higgins and Anderson (1931). SO group received the same procedure as for the PH group without liver removal. Four rats were anesthetized and sacrificed at each of the following time points: 0, 2, 6, 12, 24, 30, 36, 72, 120 and 168 h after PH, respectively, and their livers were instantly removed and stored at − 80°C for use. 2.4. Rat genome 230 2.0 microarray detection Total RNA was extracted according to the manual of Trizol reagent (Invitrogen Corporation, Carlsbad, California, USA) and purified following the RNeasy mini protocol (Qiagen, Inc, Valencia, CA, USA). The quality of total RNA was assessed by optical density measurement at 260/280 nm and agarose electrophoresis (180 V, 0.5 h). It was regarded as qualified sample, when 28S RNA to 18S RNA is equal to 2:1. T7-oligo dT(24) (Keck Foundation, New Haven, CT) SuperScript II RT (Invitrogen Corporation, Carlsbad, CA) and 5 μg of total RNA were used to synthesize the first strand of cDNA. The second strand was synthesized using the Affymetrix cDNA single-stranded cDNA synthesis kit. The 12 μl purified cDNA and the reagents in the GeneChip In Vitro Transcript Labeling Kit (ENZO Biochemical, New York, USA) were used to synthesize biotinlabeled cRNA. The labeled cRNA was purified using the RNeasy Mini Kit columns (Qiagen, Valencia, CA). 15 μl cRNA (1 μg/μl) was incubated with 6 μl 5 × fragmentation buffer and 9 μl RNase free water for 35 min at 94 °C, and digested into 35–200 bp cRNA fragments. The prehybridized Rat Genome 230 2.0 Microarray was put into a hybridization buffer, and the hybridization was at 45 °C in a hybridization oven (Affymetrix) at 60 rpm for 16 h. The hybridized arrays were washed by wash buffer, and stained in GeneChip® Fluidics Station 450 (Affymetrix Inc., Santa Clara, CA, USA). Then the arrays were scanned and imaged with a
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Fig. 1. mRNA expression of four selected genes measured by microarrays and RT-PCR. Solid line presented the results of RT-PCR and dotted line that of Rat Genome 230 2.0 Array.
GeneChip® Scanner 3000 (Affymetrix Inc., Santa Clara, CA, USA) (Xu et al., 2008a, 2008b). 2.5. Identification of genes related to acute hepatic failure and liver regeneration Those images showing gene expression abundance were converted into signal values, signal detection values (P (present), A (absent), M (marginal)) and experiment/control values (Ri) using Affymetrix GCOS 2.0. The data of each array were initially normalized by scaling all signals to a target intensity of 200. When P value is b 0.05, it means that the gene is present (P), when b0.065, means marginal (M), and when N0.065, means marked absent (A). On the other hand, the normalized signal values in model group of LC or PH group to that in control were used to calculate the relative value, that is, ratio value of gene expression abundance. When ratio value is ≥3, it means that gene expression was significantly up-regulated, when ≤0.33, significantly down-regulated, and when 0.33–2.99, biologically non-significant. To minimize the technical errors from microarray analysis, each sample was tested at least three times using Rat Genome 230 2.0 microarray, and the average value was
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considered as a reliable value. The genes were expressed significantly at least once during CCL4-inducedAHF and were considered as AHFrelated genes, and the genes which have been significantly changed during liver regeneration (LR) with significant difference (0.01 ≤ P b 0.05) or extremely significant difference (P ≤ 0.01) between PH and SO, as LR-related genes. 2.6. Gene ontology analysis of genes related to acute hepatic failure and genes related to liver regeneration In order to compare expression patterns of AHF-related genes with those of LR-related genes, we employed k-means clustering to classify the genes involved in AHF or in LR (Fig. 5). EASE (Expressing Analysis Systematic Explorer) is a network platform for functional enrichment analysis characterized by providing some statistical tests to determine whether the GO categories are over-represented or not. Firstly, the genes in every cluster were mapped to their corresponding unique genes, and GO analysis assigned each gene to a class of biological function. Then EASE analysis was conducted to identify GO categories in every cluster that are over-represented according to EASE
Number
350 300 250 200 150 100 50 0
2
3
6
12
24
30
36
48
72
120
168
Rcovery time(h) after Acute hepatic failure(AFH)/ partial hepatectomy(PH) Fig. 2. Number of expressed genes related to acute hepatic failure and that of liver regeneration. □ Number of up-regulated genes related to AHF, related to AHF, Number of up-regulated genes related to LR and Number of down- regulated genes related to LR.
Number of down-regulated genes
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3. Results 3.1. Comparative analysis of the detection results of real-time polymerase chain reaction and that of microarray
Fig. 3. The distribution of genes associated with acute hepatic failure (AHF) and those associated with liver regeneration (LR). 552 LR-specific genes were composed of 362 up-regulated genes and 190 down-regulated, and 626 AHF-specific genes, 413 up-regulated genes and 213 down-regulated.
score (a modified Fisher's exact test), with the Bonferroni multiple testing correction (Hosack et al., 2003; Huang et al., 2009; Out et al., 2007). The GO categories with EASE scores of b 0.05 are considered to be significantly over-represented, and the GO categories with EASE scores of b0.01 are considered to be extremely significantly over-represented. 2.7. Quantitative RT-PCR Four genes, related to inflammation and stimulus responses, drug metabolism, gene transcription, proliferation and apoptosis of cells and some transcription factors, were selected for RT-PCR assays to verify the chip data. The primers were designed with Primer Express 2.0 software according to mRNA sequences of target genes A2M, SPP1, CYP1A1 and TRIM24 (GenBank number: NM_012488, NM_012881, NM_012540 and NM_001044266) and synthesized by Shanghai Generay Biotech Co., Ltd. The gene-specific primers were as follows: forward primer 5′-CGAACATCCGTAAACCCAAAGTC-3′ and reverse primer 5′-GCTG AGTCCACCACCACCAAGTC-3′ for A2M, forward primer 5′-TGATGA CGACG- ACGATGACGATGG-3′ and 5′-ACGCTGGGCAACTGGGATGAC CTT-3′ reverse primer for SPP1, forward primer 5′-AGGACAGGAGG CTGGACGAGA-3′, and reverse primer 5′-ATGGTGAATGGGACAAAGGAT-3′ for CYP1A1, forward primer 5′-CAGTGGGAGGGTCTTACAA TC-3′ and reverse primer 5′-CTGGCCAGGGTCTACACTTG-3′ for TRIM24. Total RNA (2 μg) was reverse-transcripted using random primers and reverse transcription kit (Promega). First-strand cDNA samples were subjected to quantitative PCR amplification by using SYBR® Green I on the Rotor-Gene Rotor-Gene 3000A (Corbett Robotics, Brisbane, Australia), and the reaction condition was 95 °C 2 min, 95 °C 15 s, 60 °C 15 s, 72 °C 30 s, 40 cycles. Every sample was analyzed in triplicate. Standard curves were generated from five repeated ten-fold serial dilutions of cDNA, and the copy numbers of target genes in every milliliter of the sample were calculated according to their corresponding standard curves (Wang and Xu, 2010).
To confirm the results of the microarray analysis, RT-PCR assays were used to detect the expression changes of the genes including A2M and TRIM24 (these two genes are both related to AHF and LR), and SPP1 and CYP1A1 (they are only related to AHF), and at 3, 6, 12, 24, 48 and 72 h after CCl4 treatment and that in regenerating livers at 0, 2, 6, 12, 24, 30, 36, 72, 120 and 168 h after PH. Even though the abundance relative expression values of the genes detected by above two methods were not all the same, expression trends were generally consistent, suggesting that the array detection results were reliable (Fig. 1). 3.2. Comparative analysis of gene expression profiles of rat acute hepatic failure and that of rat liver regeneration Rat Genome 230 2.0 array was used to detected the gene expression profiles of acute hepatic failure (AHF), showing that a total of 1012 genes, including 631 up-regulated and 381 down-regulated genes, has significantly changed during AHF occurrence. Among them, 207genes were significantly changed at 3 h after CCl4 treatment, 438 genes at 6 h, 470 genes at 12 h, 640 genes at 24 h, 427 genes at 48 h, and 269 genes at 72 h (Fig. 2). The gene expression profiles of rat liver regeneration (LR) were also detected as above, and it was found that 948 genes, composed of 611 up-regulated and 337 down-regulated genes, were significantly expressed during LR. In detail, 185 genes were significantly expressed at 2 h after PH, 314 genes at 6 h, 384 genes at 12 h, 297 genes at 24 h, 369 genes at 30 h, 253 genes at 36 h, 405 genes at 72 h, 92 genes at 120 h, and 81 genes at 168 h (Fig. 2). It was obvious that the up-regulated genes kept more than the down-regulated in the two processes, and that the AHF-associated genes were expressed mainly at the progressing phase (12–48 h) of AHF occurrence, while LR-associated genes mainly at the progressing phase (6–72 h) after PH. Moreover, 626 genes were the AHF-specific genes, 552 genes were the LR-specific and 396 genes were the common genes (Fig. 3). To compare AHF with LR on the whole, this study carried out H-clustering analysis. The results showed that 3, 6, 12 h and 24 h of AHF occurrence were clustered, so were 48 and 72 h of AHF occurrence, 6 and 12 h, 2 and 168 h, 72 and 120 h, 24, 30 and 36 h during LR (Fig. 4). It was clear that some time points of AHF and those of LR were always highly correlated, though their gene expression profiles were different on the whole. Therefore, the correlation between their gene expression profiles needed a further exploration (Fig. 4). 3.3. Comparison of expression patterns of AHF-related genes with those of LR-related genes In order to explore the similarities and the differences between the expression patterns of AHF-related genes and those of LR-related genes, we looked up the expression changes of 1022 AHF-related genes during
Fig. 4. A cladogram about expression time correlation of acute liver failure (AHF)-related genes and liver regeneration (LR)-related genes. Symbols in red represent the expression time points of AHF-related genes and those in blue the expression time points of LR-related genes.
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Fig. 5. Global comparison of gene expression patterns of AHF-related genes with those of LR-related genes. A. H-cluster; B. Gene expression patterns of AHF (left panel) and LR (right panel).
LR and those of 948 LR-related genes in the occurrence of AHF, then a total of 1574 genes were obtained with expression values at 14 time points (3, 6, 12, 24, 48 and 72 h after CCl4 treatment and 2, 6, 12, 24, 30, 36, 72, 120, and 168 h of LR). Subsequently, 1574 genes above were categorized into 6 clusters by k-means (Fig. 5A). Of them, Cluster 1 contained 251 genes which were significantly changed in expression, peaking at 6 h during AHF occurrence while up-regulated slightly at the priming phase after PH. Cluster 2 contained 145 genes which were significantly down-regulated with the expression peak at 3 h during AHF occurrence, but were up-regulated with an expression peak at 2 h during LR. Cluster 3 involved 531 genes, which were decreased in the two processes, peaking at 24 h during AHF occurrence and at 12 and 30 h during LR. Cluster 4 contained 263 genes, which were remarkably up-regulated at the recovery phase, peaking at 48 h during AHF occurrence, but upregulated at the progressing phase, peaking at 24 and 36 h during LR. 101 genes were embodied in cluster 5, and they displayed increased
expression with a peak at 24 h during AHF occurrence, and so did they with peaks at 6 h, 30 h, and 72 h during LR (Fig. 5B). 3.4. Expression patterns and function clustering of AHF-related genes and LR-related genes According to gene ontology database (GO), AHF-related genes and LR-related genes were involved in 23 kinds of physiological activities including stimulus, inflammation and immune response, material and energy metabolism, cell proliferation, growth, differentiation, development, apoptosis, migration and adhesion. This study performed expressing analysis systematic explorer (EASE) analysis on the genes sets of clusters 1–5 in Fig. 5, and the over-represented GO categories were selected from each cluster according to the EASE scores (Table 1). In each category, the number of genes precedes the modified EASE score (P value). These categories with EASE scores of b0.05 represented classes of genes in which
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C. Xu et al. / Gene 528 (2013) 59–66 Table 1 (continued)
Table 1 Expression patterns and function clustering of AHF-related genes and LR-related genes in rat. Cluster enriched biological process
No. of genes
P-value
C1 Response to organic substance Response to endogenous stimulus Response to organic cyclic substance Response to hormone stimulus Response to abiotic stimulus Response to oxidative stress Response to cAMP Response to steroid hormone stimulus Response to inorganic substance Regulation of apoptosis Regulation of programmed cell death Regulation of cell death Transcription C2 Ion homeostasis Response to organic substance Response to hormone stimulus C3 Amine catabolic process Carboxylic acid biosynthetic process Carboxylic acid catabolic process Cellular amino acid derivative metabolic process Cofactor metabolic process Energy derivation by Oxidation of organic compounds Energy reserve metabolic process Fatty acid metabolic process Glucose metabolic process Lipid biosynthetic process Lipid catabolic process Organic acid biosynthetic process Organic acid catabolic process Oxidation reduction Response to drug Response to endogenous stimulus Response to extracellular stimulus Response to organic substance Response to steroid hormone stimulus Steroid metabolic process Vitamin metabolic process Xenobiotic metabolic process C4 Cell cycle Cell cycle phase Cell cycle process Cell division Chromosome organization DNA metabolic process DNA repair DNA replication DNA-dependent DNA replication M phase M phase of mitotic cell cycle Microtubule-based process Mitotic cell cycle Nuclear division Organelle fission Regulation of cell cycle Response to DNA damage stimulus C5 Biological adhesion Cell adhesion Cell migration Cell motion Chemotaxis Defense response Defense response to bacterium Immune response Inflammatory response Leukocyte activation Localization of cell Positive regulation of immune system process Positive regulation of response to stimulus Regulation of cell proliferation Regulation of inflammatory response Regulation of leukocyte activation Response to bacterium Response to hormone stimulus Response to molecule of bacterial origin
48 34 19 29 24 16 10 19 18 30 30 30 31 11 22 14 17 27 22 25 24 14 9 33 19 35 16 27 22 81 35 45 33 63 28 34 18 9 61 44 53 28 26 49 24 33 17 37 24 22 35 23 23 22 28 32 32 26 31 22 52 13 47 34 24 26 29 21 43 14 20 28 32 21
2.40E-11 1.50E-09 3.30E-08 8.40E-08 5.70E-07 8.10E-07 1.60E-06 3.90E-06 5.20E-06 7.80E-06 1.00E-05 1.10E-05 3.30E-06 2.60E-03 4.00E-05 4.60E-04 3.30E-11 1.10E-13 2.90E-13 7.10E-11 1.60E-08 1.10E-05 1.70E-05 2.10E-16 2.90E-06 8.90E-13 6.50E-06 1.10E-13 2.90E-13 6.00E-32 6.30E-11 1.90E-09 1.50E-10 2.00E-10 7.20E-08 7.70E-19 4.00E-11 2.00E-07 8.30E-41 2.30E-35 1.30E-37 3.10E-22 3.00E-11 3.50E-33 3.30E-15 3.70E-31 1.60E-20 1.90E-31 6.60E-21 1.10E-12 6.20E-25 5.60E-20 2.10E-19 1.00E-10 1.00E-15 1.40E-06 1.40E-06 1.60E-08 4.40E-07 1.60E-15 1.00E-21 5.00E-06 3.20E-17 1.40E-16 7.60E-09 1.50E-06 1.20E-11 2.80E-06 8.10E-08 1.30E-07 3.80E-08 7.70E-12 1.00E-05 1.10E-10
Cluster enriched biological process Response to organic substance Response to wounding
No. of genes
P-value
58 50
7.40E-10 5.20E-19
P-value represents EASE score (a modified Fisher's exact test).
individual members occurred more often than would be expected by a random distribution of genes. Obviously, cluster 1 (C1) was enriched with the genes in categories of stimulus response and cell apoptosis, etc. The genes in cluster 2 (C2) were functionally classified into the categories of regulation of homeostasis and hormone stimulation, etc. A higher proportion of genes in cluster 3 (C3) were associated with material and energy metabolism and oxidation reduction, etc. Cell cycle and cell proliferation-related genes were predominant in cluster 4 (C4). Cluster 5 (C5) was full of some genes regulating cell proliferation and genes related to immunity, inflammation and trauma responses, cell and migration, etc. (Table 1). 4. Discussion In the past, acute hepatic failure (AHF) and liver regeneration (LR) have aroused great attention because of their close association with stimulus and inflammation responses, rapid proliferation and growth of cells. Consequently, many researchers attempted to find out the similarities and differences between their cellular processes, in order to elucidate the mechanism of AHF (Li et al., 2010; Xu et al., 2007). In this study, Rat Genome 230 2.0 array was used to detect gene expression profiles of liver tissues from the carbon tetrachloride (CCl4)-treated rats and regenerating livers at different time points after partial hepatectomy (PH), and it was found that 1022 genes were associated with AHF occurrence and 948 genes with LR. Among them, 396 genes were the common genes. GO analysis showed that stimulus, immune and inflammatory responses, material metabolism and transport, cell proliferation, growth, differentiation, development, migration and adhesion were involved both in AHF occurrence and in LR, but their degrees of correlation with AHF and with LR were different (Lockhart et al., 2003; Rosen et al., 2008; C.S. Xu et al., 2005; Z. Xu et al., 2005). Previous studies have proven that hepatic cells sensed the decrease in tissue oxygenation, then activated hypoxia-inducible signaling pathways, and promoted liver cell survival (Plock et al., 2007). In this study of 51 stimulus-related genes, blood bilirubin-regulating gene ABCC3 (Chang et al., 2004), CYP11A1 involved in stress response, and insulin-induced protein homology INSIG1, were up-regulated in AHF occurrence. Early growth factor gene EGR1, eukaryotic translation initiation factor gene EIF2B3, insulin-like growth factor binding protein gene IGFBP1, and transforming growth factor gene TGFB3 were up-regulated in AHF occurrence, but showed insignificant changes in LR. Therefore, t the regulation mechanisms of stimulus response were indicated to be different in the two processes. In addition, among 24 genes related to regulation of apoptosis, glutamate cysteine ligase modifier subunit GCLM, nuclear protein gene NUPR1, were up-regulated in AHF occurrence, while down- regulated in LR. The above-mentioned genes were rich in cluster 1 (Table 1), and significantly up-regulate in AHF occurrence, but downregulated or showing insignificant changes in LR. It was suggested that stimulus response, cell apoptosis, in AHF occurrence were stronger than in LR, meaning that AHF occurrence was regulated by the apoptosisrelated genes above, which was consistent with the research results by Singhal et al. (2009). This study found that 33 genes were involved in regulating ion and hormone homeostases. Of them, calcium release channel gene RYR3, sodium channel alpha subunit SCN8A, one member of solute carrier family SLC34A, tachykinin gene TAC1, lysyl oxidase LOX, transforming growth factor beta receptor TGFBR2, and interleukin receptor gene IL1R1 were down-regulated in AHF occurrence, but up-regulated in LR. The 33
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genes above were predominant in cluster 2 (Table 1), implying that calcium, sodium and hormone homeostases differed between AHF occurrence and LR, when subjected to different external stimuli. Xu et al. (2008a, 2008b) and Guo and Xu (2008) hold that carbohydrates, lipid, amino acid and nucleic acid metabolisms were enhanced, and were the basis of material and energy metabolisms during LR. According to this study, cluster 3 was enriched with genes related to metabolism, oxidation reduction and drug response (Table 1). They were down-regulated at 6–48 h of the two processes with more genes in LR than in AHF occurrence, and the expression abundance of these genes were greater, which meant that impaired liver function significantly affected material metabolism both in AHF occurrence and in LR (Jiang et al., 2007). In detail, amine catabolism-related gene DMGDH, kynurenine 3-hydroxylase genes KMO and KYNU, glutathione transferase gene LOC681913, oxidation reduction-related alcohol dehydrogenase genes ADH1 and ADHFE1, and aldehyde-keto reductase family member gene AKR1B7 were down-regulated both in AHF and in LR, which suggested that the level of oxidation reduction in the two processes was decreased. In addition, lipid metabolism-related genes, including sterols isomerase gene EBP, enoyl acylating coenzyme A reductive enzyme gene GPSN2, 3-hydroxy-3-methylglutaryl-Coenzyme A synthase gene HMGCS1, glycometabolism-related genes including glucokinase regulatory protein gene GCKR and hepatocyte nuclear factor gene ONECUT1, and amino acid metabolism-related genes including picolinate carboxylase gene ACMSD and apolipoprotein gene APOA2 were down-regulated at many time points of AHF occurrence, while showing insignificant changes in LR, which indicated that carbohydrates, lipid and amino acid metabolisms in LR were stronger than in AHF occurrence (Schneeweiss et al., 1993; Xu and Chang, 2008). Studies showed that both AHF and LR included cell proliferation and damage repair. Yang et al. (2009) found that LR would occur at a relative late time point when expression of cell cycle protein cyclin D1 was decreased. Hence, it was significant to explore the similarities and differences of their cell proliferations (Xu et al., 2007). In this study, 126 genes associated with cell cycle and cell proliferation were harbored in cluster 4 (Table 1). Among them, cancer-induced gene BRCA2, replication initiation complex subunit ORC6L, cell cyclin genes CCNA2 and CCNE2, cyclin-dependent kinase CDC2A, began to be up-regulated from 24 h with a peak at 48 h during AHF occurrence, while peaked at 24 and 72 h during LR, which agreed with the finding that hepatocyte proliferation occurred at 24 h, and the proliferation peak of non-parenchymal liver cells occurred late during LR (Koniaris et al., 2003; Palmes and Spiegel, 2004). As a whole, cell division machinery worked actively in cell proliferation and growth of AHF and LR. In addition, DNA repair gene BLM, MCM10 involved in DNA replication micro-chromosomal repair protein, and inhibition apoptosis TBC1 family member gene TBC1D12 were up-regulated in LR, while down-regulated or showing insignificant changes in AHF occurrence. Based on expression differences of these genes in above two events, it was inferred that DNA damage repair mechanism was poor in AHF occurrence, causing a high error rate of DNA replication, and that the regulation of cell proliferation in LR was relatively perfect, which was consistent with the previous studies (Xu et al., 2007). Perhaps it is the real reason that causes recovery of liver injury slow in AHF, but fast in LR. It is generally believed that cell adhesion and migration are closely related to infiltration and metastasis of immune and inflammatory cells in AHF occurrence, meanwhile, they were important to structure–function rebuilding in LR (Li et al., 2007). This study found that 159 genes related to immune and inflammation responses, cell adhesion and migration had a high proportion in cluster 5 (Table 1). Of them, laminin gene LAMC1, former calcium adhesion protein gene FAT1, and adhesion molecule CD24 were up-regulated in AHF occurrence, but displayed nonsignificant changes in LR, which meant that cell adhesion and migration in AHF occurrence were stronger than in LR. Mookerjee et al. (2007) found that inflammatory cell could produce inflammatory cytokines and chemokines in AHF occurrence, and
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reactive oxygen species and other substances produced by these factors were detrimental to cell survival and would increase the risk of AHF occurrence (Jansen et al., 2009). Thus, the differences between inflammatory response in liver cells to external stimulation in AHF occurrence and that in LR deserved a further study (Taub et al., 1999; Wang et al., 2009). This study demonstrated that of 144 inflammation-related genes, tumor necrosis factor genes TNF and TNF14, interleukin gene IL1B promoting the secretion of cytokines, RT1-DA and RT1-M3 promoting antigen presentation showed insignificant changes in AHF occurrence, but were up-regulated in LR, which indicated that as liver injury went, inflammatory response in AHF became weaker than in LR. Hence, it was speculated that apoptosis and necrosis of liver cells at the late phase of AHF might be caused by their decreased resistance against various stimulus. 5. Conclusion In short, this study analyzed the gene expression profiles of AHF and that of LR, and carried out functional enrichment analysis to analyze the physiological activities uncovered by the profiles. It is concluded that gene expression changes and physiological activities of AHF and those of LR not only have similarities but also differences, and we will confirm the results of this study using gene addition, knock-out, and RNAi in future. Conflict of interest There is no competing financial interests exist. Acknowledgments This work was supported by the National Basic Research 973 Preresearch Program of China, No. 2012CB722304. Meanwhile, we were grateful to Xueliang Wang for his revising the English manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2013.07.023. References Ambrosino, G., et al., 2003. Hepatocyte transplantation in the treatment of acute liver failure: microencapsulated hepatocytes versus hepatocytes attached to an autologous biomatrix. Cell Transplant. 12, 43–49. Chang, T.H., Hakamada, K., Toyoki, Y., Tsuchida, S., Sasaki, M., 2004. Expression of MRP2 and MRP3 during liver regeneration after 90% partial hepatectomy in rats. Transplantation 77, 22–27. Cheng, W.T., Tian, D.Y., 2010. Effects and mechanism of endotoxemia on carbohydrate metabolism in D-GalN-reduced acute hepatic failure rats. Chin. J. Integr. Tradit. West. Med. 20, 38–40. Fausto, N., Campbell, J.S., Riehle, K.J., 2006. Liver regeneration. Hepatology 43, 45–53. Felipo, V., Butterworth, R.F., 2002. Mitochondrial dysfunction in acute hyperammonemia. Neurochem. Int. 40, 487–491. Gao, C.F., Zhou, F., Wang, H., Huang, Y.F., Ji, Q., Chen, J., 2009. Genetic recombinant expression and characterization of human augmenter of liver regeneration. Dig. Dis. Sci. 54, 530–537. Guo, G.B., Xu, C.S., 2008. Expression profiles of the organic acid metabolism-associated genes during rat liver regeneration. Amino Acids 34, 597–604. Higgins, G.M., Anderson, R.M., 1931. Experimental pathology of the liver: restoration of the liver of the white rat following partial surgical removal. Arch. Pathol. Lab. Med. 12, 186–202. Hosack, D.A., Dennis Jr., G., Sherman, B.T., Lane, H.C., Lempicki, R.A., 2003. Identifying biological themes within lists of genes with EASE. Genome Biol. 4, 70. Huang, D.W., Sherman, B.T., Lempicki, R.A., 2009. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57. Ichida, T., 2003. Artificial liver support system for fulminant hepatic failure as bridgehouse to living donor liver transplantation. Intern. Med. 42, 967–970. Jansen, P.A.M., et al., 2009. Expression of the vanin gene family in normal and inflamed human skin: induction by proinflammatory cytokines. J. Invest. Dermatol. 129, 2167–2174. Jiang, J.T., Xu, N., Zhang, X.Y., Wu, C.P., 2007. Lipids changes in liver cancer. J. Zhejiang Univ. Sci. B 8, 398–409.
66
C. Xu et al. / Gene 528 (2013) 59–66
Jin, S.Z., Meng, X.W., Han, M.Z., Sun, X., Sun, L.Y., Liu, B.R., 2009. Stromal cell derived factor-1 enhances bone marrow mononuclear cell migration in mice with acute liver failure. World J. Gastroenterol. 7, 2657–2664. Kaido, T., Imamura, M., 2001. Hepatocyte growth factor: clinical implications in hepatobiliary pancreatic surgery. J. Hepatobiliary Pancreat. Surg. 8, 65. Koniaris, L.G., McKillop, I.H., Schwartz, S.I., Zimmers, T.A., 2003. Liver regeneration. J. Am. Coll. Surg. 197, 634–659. Li, H.L., Chen, X.G., Zhang, F.C., Ma, J., Xu, C.S., 2007. Expression patterns of the cell junction-associated genes during rat liver regeneration. J. Genet. Genomics 34, 892–908. Li, T., Wan, B., Huang, J., Zhang, X., 2010. Comparison of gene expression in hepatocellular carcinoma, liver development, and liver regeneration. Mol. Genet. Genomics 283, 485–492. Lockhart, A.C., Tirona, R.G., Kim, R.B., 2003. Pharmacogenetics of ATP-binding cassette transporters in cancer and chemotherapy. Mol. Cancer Ther. 2, 685–698. Mookerjee, R.P., et al., 2007. Inflammation is an important determinant of levels of the endogenous nitric oxide synthase inhibitor asymmetric dimethylarginine (ADMA) in acute liver failure. Liver Transpl. 13, 400–405. Out, H.H., et al., 2007. Restoration of liver mass after injury requires proliferative and not embryonic transcriptional patterns. J. Biol. Chem. 282, 11197–11204. Palmes, D., Spiegel, H.U., 2004. Animal models of liver regeneration. Biomaterials 25, 1601–1611. Park, J.H., et al., 2012. Protective effect of melittin on inflammation and apoptosis in acute liver failure. Apoptosis 17, 61–69. Plock, J., et al., 2007. Activation of non-ischemic, hypoxia-inducible signalling pathways up-regulate cytoprotective genes in the murine liver. J. Hepatol. 47, 538–545. Rosen, M.B., et al., 2008. Toxicogenomic dissection of the perfluorooctanoic acid transcript profile in mouse liver: evidence for the involvement of nuclear receptors PPAR alpha and CAR. Toxicol. Sci. 103, 46–56. Schneeweiss, B., et al., 1993. Energy metabolism in acute hepatic failure. Gastroenterology 105, 1515–1521. Singhal, S., Jain, S., Kohaar, I., Singla, M., Gondal, R., Kar, P., 2009. Apoptotic mechanisms in fulminant hepatic failure: potential therapeutic target. Appl. Immunohistochem. Mol. Morphol. 17, 282–285.
Taub, R., 2004. Liver regeneration: from myth to mechanism. Nat. Rev. Mol. Cell Biol. 5, 836–847. Taub, R., Greenbaum, L.E., Peng, Y., 1999. Transcriptional regulatory signals define cytokinedependent and -independent pathways in liver regeneration. Semin. Liver Dis. 19, 117–127. Tomiya, T., Omata, M., Imamura, H., Fujiwara, K., 2008. Impaired liver regeneration in acute liver failure: the significance of cross-communication of growth associated factors in liver regeneration. Hepatol. Res. 38, 29–33. Wang, G.P., Xu, C.S., 2010. Reference gene selection for real-time RT-PCR in eight kinds of rat regenerating hepatic cells. Mol. Biotechnol. 46, 49–57. Wang, W.B., Fan, J.M., Zhang, X.L., Xu, J., Yao, W., 2009. Serial expression analysis of liver regeneration-related genes in rat regenerating liver. Mol. Biotechnol. 43, 221–231. Xu, C.S., Chang, C.F., 2008. Expression profiles of the genes associated with metabolism and transport of amino acids and their derivatives in rat liver regeneration. Amino Acids 34, 91–102. Xu, C.S., et al., 2005a. Expressed genes in regenerating rat liver after partial hepatectomy. World J. Gastroenterol. 11, 2932–2940. Xu, Z., Chen, L., Leung, L., Yen, T.S., Lee, C., Chan, J.Y., 2005b. Liver-specific inactivation of the Nrf1 gene in adult mouse leads to nonalcoholic steatohepatitis and hepatic neoplasia. Proc. Natl. Acad. Sci. U. S. A. 102, 4120–4125. Xu, C.S., Zhang, S.B., Chen, X.G., Rahman, S., 2007. Correlation analysis of liver tumor-associated genes with liver regeneration. World J. Gastroenterol. 13, 3323–3332. Xu, C.S., Lin, F., Qin, S.W., 2008a. Relevance between lipid metabolism-associated genes and rat liver regeneration. Hepatol. Res. 38, 825–837. Xu, C.S., Zhang, S.B., Yang, Z.L., Cui, S.N., Zhang, M., 2008b. The expression changes of genes associated with protein metabolism, folding, transport, localization and assembly during rat liver regeneration. Fen Zi Xi Bao Sheng Wu Xue Bao 41, 107–119. Yang, R.K., Miki, K., He, X., Killeen, M.E., Fink, M.P., 2009. Prolonged treatment with Nacetylcysteine delays liver recovery from acetaminophen hepatotoxicity. Crit. Care 13, 55. Yu, C.H., Chen, H.L., Chen, Y.H., Chang, M.F., Chien, C.S., Chang, M.H., 2009. Impaired hepatocyte regeneration in acute severe hepatic injury enhances effective repopulation by transplanted hepatocytes. Cell Transplant. 18, 1081–1092.