Protein Profilings in Mouse Liver Regeneration after Partial Hepatectomy Using iTRAQ Technology Hui-Chu Hsieh, Yi-Ting Chen, Jen-Ming Li, Ting-Yu Chou, Ming-Fong Chang, See-Chang Huang, Tzu-Ling Tseng, Chung-Cheng Liu, and Sung-Fang Chen* Molecular Biomedical Technology Division, Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Hsinchu 310, Taiwan Received September 9, 2008
Liver is unique in its capability to regenerate after an injury. Liver regeneration after a 2/3 partial hepatectomy served as a classical model and is adopted frequently to study the mechanism of liver regeneration. In the present study, semiquantitative analysis of protein expression in mouse liver regeneration following partial hepatectomy was performed using an iTRAQ technique. Proteins from pre-PHx control livers and livers regenerating for 24, 48 and 72 h were extracted and inspected using 4-plex isotope labeling, followed by liquid chromatography fractionation, mass spectrometry and statistical differential analysis. A total of 827 proteins were identified in this study. There were 270 proteins for which quantitative information was available at all the time points in both biologically duplicate experiments. Among the 270 proteins, Car3, Mif, Adh1, Lactb2, Fabp5, Es31, Acaa1b and LOC100044783 were consistently down-regulated, and Mat1a, Dnpep, Pabpc1, Apoa4, Oat, Hpx, Hp and Mt1 were up-regulated by a factor of at least 1.5 from that of the controls at one time point or more. The regulation of each differential protein was also demonstrated by monitoring its timedependent expression changes during the regenerating process. We believe this is the first report to profile the protein changes in liver regeneration utilizing the iTRAQ proteomic technique. Keywords: Mouse liver regeneration • iTRAQ • Partial hepatectomy
Introduction Liver is unique in its ability to regenerate even in the mature stage.1,2 This makes liver regeneration an important focus in area of liver research. Determining the factors that are responsible for initiating regeneration following partial hepatectomy or toxic damage, as well as how the liver maintains differentiated functions while hepatocytes undergo cellular proliferation, is crucial for understanding the molecular bases of liver regeneration. Numerous pathways are involved in this process and the time course of major regulating events that control the replication of hepatocytes and enable this large parenchymal organ to restore its function after considerable damage or volume loss. Particular humoral agents can activate pathways that are related to liver regeneration, several of which are required to coparticipate in cell proliferation associated with liver regeneration.1-3 Tumor necrosis factor (TNF) and transforming growth factor alpha (TGF-R) serve as activators for liver regeneration pathways, which are related to further stimulate liver cell division.4 Growth factor-generated intracellular signals that trigger liver regeneration cause activation via the posttranslational modifications of latent, normally inactive transcription factors that are already present in the liver. * To whom correspondence should be addressed. Dr. Sung-Fang Chen, Molecular Biomedical Technology Division, Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Hsinchu 310, Taiwan. Tel, +886-3-5912150; fax, +886-3-5820445; e-mail,
[email protected].
1004 Journal of Proteome Research 2009, 8, 1004–1013 Published on Web 12/18/2008
Differential proteomics is a powerful tool to investigate molecular changes. Monitoring the protein expression can elucidate crucial information about living systems. Various approaches for measuring changes in protein expression are recently developed and available. These are generally categorized as gel-based and liquid chromatography (LC)-based approaches. These methods are usually followed by mass spectrometric analysis. The gel-based approach has been long established. The conventional 2-D PAGE procedure followed by mass spectrometry is widely implemented and practiced in proteomic studies.5-9 The high-resolution 2D-PAGE is popularly used for separating protein mixtures before image analysis is conducted for relative protein quantification and mass spectrometric analysis to identify the proteins. However, it is labor-intensive, and suffers from variations among gels, requiring replicate runs, and powerful imaging software to average and compare quantitative results. Although the gel-to-gel variations could be reduced by using DIGE system,8,9 there are still some limitations in this approach, concerning the detection of hydrophobic proteins and proteins of extreme size and pI values. The limitations of 2D-PAGE are largely overcome by the LCbased approach, which is becoming increasingly popular. Sample or the LC-based approach could be stable isotope labeling or label-free. Label-free LC-MS approach was accomplished by measuring and comparing the mass spectrometric ion intensities of peptide that representing a particular 10.1021/pr800696m CCC: $40.75
2009 American Chemical Society
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Protein Profilings in Mouse Liver Regeneration 10-12
protein. Without having isotope tags that served as internal standards, the results were generally least accurate and the experimental procedures had to be carefully conducted. Nonetheless, a few advantages, including simplicity, cost effectiveness and unlimited number of experiments can be compared to make this label-free approach still worth considering. There are three varieties of stable isotope labeling approaches, including stable isotope labeling techniques with amino acids in cell culture (SILAC), isotope-coded affinity tags (ICAT) and isobaric tags for relative and absolute quantitation (iTRAQ), which were currently used in differential proteomics. SILAC, first introduced by Mann’s group, relies on the metabolic incorporation of a given “light” or “heavy” form (through isotope) of amino acid into the proteins. After a number of cell divisions, each instance of this particular amino acid is replaced by its isotope-labeled analogue. The cells were then harvested and analyzed by mass spectrometry to determine their protein ratios and identities.13,14 This technique is applied to study proteome dynamics, but may not be suitable for differential proteomics in tissues or body fluids. The isotope-coded affinity tags (ICAT) and its successor cleavable ICAT techniques are both LC/MS-based and were first developed by Aebersold’s group and Applied Biosystems, Inc. (ABI). They rely on the stable isotope tag labeling of cysteine residues of paired protein samples. Labeled samples are then mixed and digested, before undergoing several steps of LC fractionation and purification. The semiquantitative analysis of proteins is achieved by calculating the peak intensities of correlated peptides obtained by MS and their sequences are identified by tandem MS.15,16 A new variation of ICAT technology called isobaric tags for relative and absolute quantitation (iTRAQ, also from ABI) has recently attracted much attention and already been applied in various studies.17-21 It is a 4-plexed protein quantitation strategy that utilizes an approach that is similar to ICAT, but with different isotope-tagged reagents, labeled on amine groups rather than cysteine residues. Peptides labeled with these isobaric tags are indistinguishable in the MS survey scan. Fragmentation under MS/MS enables quantitative information to be obtained from low-mass signature ions (m/z from 114 to 117) and regularly fragmented ions (-b, -y types) for protein identification. In this study, iTRAQ-based differential proteomics was applied to investigate liver regeneration-related protein and related mechanisms with a partial hepatectomy (PHx) mouse model. PHx is a classic experimental model of rapid liver cell proliferation, and has been conventionally employed for decades to probe the mechanism of liver regeneration.2 The translational stages in the regenerating liver provide useful information on these issues. Liver regeneration includes three steps: (1) initiation step, (2) proliferation step and (3) termination step.22 The initiation step is characterized by priming of quiescent hepatocytes by factors such as TNF-R, IL-6, and nitric oxide (NO). This results in induction of hepatocytes to become sensitive to growth factors and competent for replication.22 The proliferation is the step that hepatocytes enter into the cell cycle’s G1-phase and progress to DNA synthesis after the stimulation of various growth factor. In the animal model, DNA synthesis starts 12-16 h after the standard partial hepatectomy and peaks at 24-48 h. The onset of mitosis follows 6-8 h later reaching its maximum 48 h after surgery. The original organ mass is almost restored in 3 days, but the histology and function are reestablished 8-10 days after surgery.22 It has been proven that
hepatocyte growth factor, transforming growth factor, epidermal growth factor, tumor necrosis factor-alpha, interleukins -1 and -6 are the main growth and promoter factors secreted after hepatic injury.4,22 After restoring original mass, a stop signal should be introduced to keep the regenerated liver in an appropriate size. However, the molecular mechanisms involved in the termination step of liver regeneration are not clearly known and only little information is available.22 There are some works which have already presented the proteomic profiling of liver development or regeneration.23-26 Sun et al. identified 24 differentially expressed proteins in rat livers at 1 h after partial hepatectomy. Those proteins are involved in functions of metabolism, detoxification, and inflammation.23 Guo et al. analyzed proteomic changes in rat livers at 7 h after PHx and identified 38 differential spots. Some of the differential proteins were associated with stress defense, lipid metabolism, and macromolecular biosynthesis, while the others were shown to be involved in regulating transcript factors associated with liver regeneration.24 Changes in protein expression in mouse livers at 6 and 12 h after partial hepatectomy were analyzed by Strey et al. Twelve up-regulated proteins were identified and the results suggested that liver regeneration following partial hepatectomy affects various signaling and metabolic pathways.25 Sun et al. analyzed the proteomic changes in mitochondria of livers at 24 h after 70% PHx. They identified 22 differentially expressed proteins associated with carbohydrate metabolism, lipid metabolism, the respiratory chain and oxidation-phosphorylation, biotransformation and other metabolic pathways.26 However, most of the studies focus on the early changes (within 24 h) after treatment. The regenerating process takes few days to fully restore liver mass. Molecular events which happened in the middle and later stages of regeneration were another important issues to be investigated. The feasibility of iTRAQ technology with multiple samples is ideally suited for investigating the regeneration process. A mouse liver proteome was elucidated and differential proteins were presented using iTRAQ technology in this study.
Experimental Procedures PHx Mouse Model. Female C57BL/6 mice were obtained from the National Laboratory Animal Center, Taiwan. All animals were kept in a temperature-controlled environment. They were cared for according to the guidelines of the Taiwan Animal Technology Institute. Mice of ages 8-10 weeks were subjected to two-thirds PHx under anesthesia. Two mice without PHx were used as control. Six mice had PHx proceeded by liver regeneration for 24, 48 and 72 h, respectively. Two mice were sacrificed at each time point and livers were resected and frozen in liquid nitrogen. Totally, eight mice were analyzed in this study. Sample Preparation, iTRAQ Labeling, and Peptide Separation. Mice were separated into two groups, Group 1 and 2. Each group contained one control mouse and three mice harvested at 24, 48 and 72 h, respectively, after PHx. Livers in Group 1 were triply labeled with iTRAQ reagents and analyzed by LCMS to investigate the experimental reproducibility. Livers in Group 2 were used for one additional iTRAQ quantitative analysis. The frozen livers were first pulverized to a powder using a mortar and pestle that had been precooled using liquid nitrogen. The liquid nitrogen was then evaporated, and the powdered tissue was separated in tubes and stored at -80 °C. Twenty volumes (w/v) of RIPA lysis buffer (50 mM Tris, 150 Journal of Proteome Research • Vol. 8, No. 2, 2009 1005
research articles mM NaCl, and 1% NP-40 at pH 7.6) was added to the powdered tissue and the sample was incubated at room temperature for 1 h. Samples were centrifuged at 12 000 rpm for 10 min and the supernatants were extracted for acetone precipitation by adding 6 vol of cold acetone to the sample tubes. Tubes were incubated at -20 °C until the precipitate formed. After the acetone had been decanted, pellets were resuspended with 0.1% SDS in dissolution buffer (provided by iTRAQ Reagents Kit). The total protein contents were determined using Coomassie Plus Protein Assay Reagent (PIERCE, Rockford, IL). A total of 100 µg of protein from each liver tissue was denatured, reduced and the cysteines were blocked, as described in the iTARQ protocol (Applied Biosystems, Foster City, CA). Ten microliters of 1 µg/µL trypsin solution was added to each tube and incubated at 37 °C overnight. Tryptic peptides from control liver and PHx tissues after regeneration for 24, 48 and 72 h were labeled with 114.1, 115.1, 116.1 and 117.1 iTRAQ tags, respectively. The labeled samples were pooled and acidified by mixing with 10 mM phosphoric acid to a total volume of 4.0 mL for strong cation exchange (SCX) chromatography. The resulting sample was injected at a flow rate of 0.07 mL/min into a liquid chromatography system (Ettan, GE Healthcare Bio-Science, Umeå, Sweden) using a 2.1 mm i.d. × 200 mm length polysulfethyl A column that was packed with 5 µm, 300 Å bead (PolyLC, Inc., Columbia, MD). A guard column of the same material was plumbed upstream from the analytical column. The buffer compositions were 10 mM KH2PO4, 25% acetonitrile at pH 3.0 for buffer A and 10 mM KH2PO4, 1 M KCl, 25% acetonitrile at pH 3.0 for buffer B. The elution gradient increased linearly from 0 to 40% buffer B within 16 mL and increased to 100% buffer B in another 4 mL. A total of 30 fractions were collected and desalted using a PepClean C-18 spin column (PIERCE, Rockford, IL). The desalted peptide mixtures from each SCX fraction were dried by speed vacuuming centrifugation and then analyzed using nanoLC tandem mass spectrometry. Mass Spectrometric Analysis. All iTRAQ samples from the SCX column were dried by speed vacuuming and stored at -20 °C. Prior to reverse-phased nanoLC/MS/MS analysis, these fractions were redissolved in 20 µL buffer that contained 5% acetonitrile and 0.1% formic acid. A total of 1.4 µL of each sample was injected onto a 300 µm i.d. × 1 mm nanoprecolumn at a flow rate of 20 µL/min with a loading time of 10 min for preconcentration and cleanup. Reverse phase separation of the labeled peptide mixture was performed in a nanoHPLC system (LC Packings, Netherlands) using a C-18 column (75 µm i.d. 150 mm length, 3 µm particles) at a flow rate of 200 nL/min. The solvent system was as follows: solvent A was 0.1% (w/v) formic acid/H2O/2% (v/v) acetonitrile, and solvent B was 0.1% (w/v) formic acid /H2O/80% (v/v) acetonitrile. The gradient was isocratic with 5% solvent B, eluted with a linear gradient from 5% solvent B to 50% solvent B over 90 min; the column was then washed using 95% solvent B for 30 min and rebalanced with buffer A for 20 min. The nanoHPLC system was connected online to a hybrid LCMS/MS system (Applied Biosystems API QSTAR, MA). The LC/ MS/MS mass spectra of eluted peptides were acquired in continuous flow mode with a 10 µm i.d. fused silica tip (New Objective, MA). Online MS and tandem MS spectra were obtained using the TOF analyzer with m/z scanning ranges of 400-1200 Da for MS and 75-1500 Da for MS/MS. The information-dependent acquisition (IDA) automatically determined the two most intense ions with multiple charges (+2 ∼ 1006
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Hsieh et al. +3) in a TOF/MS survey scan. The optimized MS/MS experiments were performed on the selected ions. Mascot Database Searching. Peak-lists of all MS/MS spectra were generated and analyzed using Mascot Daemon (Matrix Science, London, U.K.; version 2.2.1) by default setting. Mascot was set up for iTRAQ 4-plex quantitation and decoy database search against IPI MOUSE database (ipi.mouse.v3.40, 53 825 entries), assuming that the digestion enzyme was trypsin with a maximum of one missed cleavage allowed. Besides, methionine oxidation was specified as variable modifications. Mascot was searched with a fragment ion mass tolerance of 0.20 Da and a parent ion tolerance of 0.20 Da. Quantitative Data Processing. All tandem mass spectra were searched against IPI mouse database (ipi.mouse.v3.40, 53 825 entries) using ProteinPilot 2.0.1 Software (Applied Biosystems, Inc.) software. Methionine oxidation was set as the variable modification for protein identification. The accuracy tolerance for both peptides and peptide fragments was set to 0.2 Da with a 95% confidence threshold. All quantitative results were calculated based on default bias-corrections applied. Western Blot Analysis. The changes in the expression of methionine adnosyltransferase 1A (Mat1a) and actin cytoplasmic 1 (Actb) were validated by Western blot analysis to verify the results obtained by iTRAQ proteomic studies. Proteins were extracted using the same procedure described in the iTRAQ labeling experiment. Fifteen micrograms of protein from each liver tissue was resolved by 12% SDS-PAGE and then transferred to polyvinylidene difluoride (PVDF) membrane. Following blocking in 5% nonfat milk, the membrane was washed with TBST buffer (20 mM Tris-HCl, pH 7.6, 137 mM NaCl, 0.1% Tween-20) and then incubated with goat anti-methionine adnosyltransferase I (Mat I/III) polyclonal antibody (Santa Cruz Biotechnology, Inc., CA) and rabbit anti-beta actin polyclonal antibody (Laboratory Frontier, Seoul, Korea) overnight. The membranes were washed again with TBST buffer and then immunostained using peroxidase-conjugated donkey anti-goat and goat anti-rabbit IgG (Jackson ImmunoResearch Laboratories, PA). The immunoreactive bands were visualized using an enhanced chemiluminescence system (Perkin-Elmer Life Sciences, MA).
Results Partial Hepatectomy Mouse Experiment. In the 2/3 partial hepatectomy operations, median and left lateral lobes were removed. The hepatocyte proliferation in the remaining liver was initiated through liver regeneration. In the first 3 days after PHx, the remaining liver exhibited an elevated rate of regeneration. Growth reached a plateau after 72 h and its mass changed little until 5-7 days after PHx (Figure 1a). Control livers and livers harvest at three time points (24, 48 and 72 h), corresponding to the period of higher growth rate during the regeneration process, were selected for proteomic studies. Protein extracted from the liver at each time point was labeled with a set of 4-plex iTRAQ reagents, following the procedure described in the previous section (Figure 1b). Figure 1c(i) displays the base peak LC/MS spectrum of a selected SCX fraction. Figure 1, panels c(ii) and c(iii), shows the results of mass spectrometric analysis for quantification (in the low mass reporter ion region) and identification. Notably, the quantification results were based on the reporter ion peak area, rather than the peak height. The overall confidence in the identification of the peptides was also improved by the enhancement
Protein Profilings in Mouse Liver Regeneration
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Figure 1. (a) Experimental model of liver regeneration. Following the 2/3 partial hepatectomy operation, the remaining liver initiated regeneration. The regeneration index is the percentage of the remaining liver mass to original liver mass. (b) Experimental design of iTRAQ analyses for mouse liver regeneration. Livers from four mice, harvested at 24, 48 and 72 h after PHx, and control livers were used for triplicate iTRAQ experiments. (c) Results of mass spectrometric analysis for quantification (in low mass reporter ion region) and identification. (i) Base peak chromatography of LC/MS run from a particular fraction. (ii) Expanded view of reporter ion region (low-mass region) in the MS/MS spectrum, showing relative abundances of signature iTRAQ ions at 114.1, 115.1, 116.1 and 117.1. (iii) MS/MS spectrum of doubly protonated peptides, FVIGGPQGDAGVTGR, identified as methionine adenosyltransferase I, alpha.
of signals from the b-ion series, obtained by the amine-specific N-terminal labeling of isobaric tag. Mouse Liver Proteome and Its Functional Categories. Information from the chemically triplicate experiments (Group 1) and one biologically replicate (Group 2) were analyzed using Mascot. The numbers of distinct peptides identified by Mascot in the runs were 1566, 2054, 1958 and 1357, yielding 486, 579, 577 and 421 proteins, respectively. The false positive rate of protein identification obtained by Mascot is 2.60%, 1.68%, 1.48% and 2.70%. After the redundancies were removed, 827 proteins were identified by the Mascot search engine with at least one peptide above the threshold (p < 0.05). Figure 2 plotted the number of peptides identified in a protein. It clearly shows that around 40∼46% of proteins were identified by a single peptide, probably because of the complexity and existence of abundance proteins. Still, more than 50% of proteins were identified by at least two distinct peptides. Approximately 17% of proteins were identified by more than five peptides, and these were mainly abundant proteins. This result was similar to that of our study in liver proteome, which were achieved by a strategy of separating intact proteins with offline multidimensional liquid chromatography (data not shown).
Figure 2. Number of distinct peptides identified in a protein. The peptides were identified using Mascot software, based on a 95% confidence level. About 40-46% of proteins were identified by single peptides. More than 50% of proteins were identified by at least one peptide. Approximately 17% of proteins were identified by more than five peptides.
Examining the proteins identified in the three chemically replicate experiments, 731 proteins were identified by Mascot search engine based on a 95% confidence level. A total of 369 proteins (50.5%, 369/731) were identified in all three experiments. There were another 173 proteins (23.7%) identified in Journal of Proteome Research • Vol. 8, No. 2, 2009 1007
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Figure 3. Reproducibility of protein identification in iTRAQ experiments. (a) An identical mouse liver regeneration specimen was processed three times with iTRAQ analyzing procedure. A total of 731 proteins were identified in Group 1. A total of 369 proteins were identified in all three experiments. There were 173 proteins identified in two of the experiments. Only 189 proteins were identified in single experiment. (b) Comparing the 731 proteins identified in the chemically triplicate experiments (Group 1) with the 421 proteins identified in a biological replicate (Group 2), there were 325 proteins identified in both groups.
Figure 4. Molecular functions of whole mouse liver proteome. The 827 proteins with functional annotations were classified according to molecular function. Since one protein may exhibit more than one molecular function, the sum of the percentages associated with all categories exceeded 100%.
two of the experiments, which added up to a total of 542 proteins (74.1%, 542/731) detected in at least two analyses. Only 189 proteins (25.9%) were identified in single experiment (Figure 3). Comparing the 731 proteins identified in the chemically triplicate experiments (Group 1) with the 421 proteins identified in the biological replicate (Group 2), there were 325 proteins identified in both groups (Figure 3). Totally, 827 distinct proteins were identified in this study. Figure 4 demonstrated the functional categories of the 827 distinct proteins identified in this study. The proteins that are involved in binding and catalytic activity were 43.6% and 37.8%, respectively. These values are not surprising since metabolism 1008
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Hsieh et al.
Figure 5. Reproducibility of analyzing the PHx induced liver regeneration by iTRAQ technique. (a) CV distribution and (b) correlation of the quantitative results between the chemically triplicate experiments and the biologically duplicate experiments.
occurs in the liver. The remaining mouse liver proteins were categorized as proteins that exhibited signal transducer, enzyme regulator, structural molecule, transporter, transcription regulator and translation regulator activities. Quantitative Proteome. To determine the reproducibility of the iTRAQ technique, the experiment was repeated three times with identical specimens. Among the identified proteins, there were 395, 394 and 358 proteins whose quantitative information was available at all the time points. A total of 584 distinct proteins were identified and quantified. Among these 584 proteins, there were 220 proteins quantified in all the three experiments. The coefficients of variation (CV) for 220 proteins quantified in all the chemically triplicate experiments were calculated to elucidate the quantitative reproducibility of the iTRAQ approach. As shown in Figure 5a, there were 60.2%, 23.6% and 9.4% of proteins which had CV values under 10%, 10-20% and 20-30%, respectively. Only 6.8% of proteins had CV value which exceeded 30%. In summary, 83.8% of the proteins had CV values under 20%, suggesting that the iTRAQ approach exhibited satisfactory reproducibility of the quantitative results for mouse liver proteome. A biological repeated experiment was conducted to evaluate reproducibility of this study. A total of 417 proteins were identified and quantified in the biologically replicate (Group 2). Among 584 and 417 proteins quantified in Group 1 and 2, 270 proteins were quantified in both groups at all the time
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Protein Profilings in Mouse Liver Regeneration points. Among these 270 proteins, there were 39.5%, 30.9% and 14.9% of proteins which had CV values under 10%, 10-20% and 20-30%, respectively. There were 14.7% of proteins with CV value which exceeded 30% (Figure 5a). The consistencies of quantitative results were further evaluated by analyzing the correlations between the chemically and biologically replicate experiments, respectively (Figure 5b). The R-values of quantitative results between two experiments in the same time points were around 0.76-0.93 for both chemically and biologically replicates. The high correlation represented high reproducibility of this study. The R-values of quantitative results between different time points were around 0.49-0.82. The lower R-values indicated that there was drastically different protein profiles between livers in different regenerating states. Differentially Expressed Proteins in PHx Induced Regenerating Livers. Differential proteins were considered significant when their expressions were consistently up- or downregulated in at least one of the time points in both of the biologically duplicate groups. Among the 270 identified proteins, there were 8 up-regulated and 8 down-regulated proteins with fold changes of 1.5 or more by comparing with the controls. Table 1 exhibited detailed information as IPI accession number, gene symbol, averaged ratio and standard deviation. The 16 differentially expressed proteins were further submitted for functional analysis with reference to the GO database from CGAP (Cancer Genome Anatomy Project). All 16 genes were functionally annotated. Intriguingly, seven of the 16 proteins were metal-ion binding proteins. Three of them, Car3, Lactb2, and Adh1, were down-regulated. Four of the eight up-regulated proteins, Hpx, Dnpep, Mat1a, Mt1, were metal-ion binding proteins. The functional annotations of the proteins were also indicated in Table 1. The averaged ratios of the differential proteins were plotted over time to elucidate the time-dependent expressional changes. The regulation pattern of each differential protein in the regenerating process could be easily identified in Figure 6. Mif drastically decreased after PHx and then slowly increased with regenerating time. Es31 and Acaa1 were down-regulated continually at 24 and 48 h, and then gradually increased after 48 h. LOC100044783, which is similar to Isopentenyl-diphosphate delta isomerase (Idi1), and Lactb2 were down-regulated at 24 h, then slightly up-regulated at 48 h and finally decreased again at 72 h. Car3, Fabp5 and Adh1 did not change much at 24 h, but were down-regulated at both 48 and 72 h. Of the 8 upregulated proteins, Mat1a and Apoa4 increased drastically and reached the maximum expressional level at 24 h, then declined as regeneration progressed. The expression of Dnpep, Pabpc1, Oat and Hp gradually increased after PHx, having highest expression at 48 h, then decreasing after 48 h. Hpx has similar expressional level with controls at 24 h and then gradually increase when regeneration progressed. Mt1 highly expressed at both 24 and 48 h, and then gradually decreased after 48 h. Western Blot Analysis of Selected Proteins. Western blot analysis was conducted to measure the expression of Mat1a and Actb in control and regenerated mouse livers, and thus validated the quantitative results obtained from iTRAQ proteomic studies. Figure 7A presented the relative expressional ratios of Mat1a and Actb determined by iTRAQ analyses. Figure 7B presented the expressional profiles of Mat1a and Actb monitored by the Western blot analysis. Similar to the iTRAQ results, Western blot analysis demonstrated that Mat1a was indeed differentially expressed among these samples, clearly
indicating that Mat1a reached the highest expression level at the 24- and 48-h points and slowly declined. The LC-MS/MS method and Western blot both showed no significant variance in Actb expression during liver regeneration.
Discussion The ability to regenerate in the mature stage makes liver regeneration an important focus in liver research. Differential proteomics is a powerful tool to investigate molecular changes between different stages. The feasibility of iTRAQ technology to simultaneously analyze multiple samples is ideally suited for investigating regeneration process. Low CV and high correlation (R) values suggested that the iTRAQ approach exhibited satisfactory reproducibility of the quantitative results for mouse liver proteome. PHx is a classic experimental model to probe the mechanism of liver regeneration, which was carried out by removing median and left lateral lobes of liver.2 However, this operation caused serious damage of liver and might induce many acute phase proteins. It was not surprising that many differential proteins identified in our study were acute phase proteins. Haptoglobin (Hp) and hemopexin (Hpx) were up-regulated and have highest expression level at late stages of liver regeneration in our study. Haptoglobin and hemopexin both belong to acute phase proteins and are induced by several cytokines.27,28 It has been demonstrated that haptoglobin and hemopexin together are essential for protection from splenomegaly and liver fibrosis resulting from intravascular hemolysis.29 Hemopexin is mainly expressed in liver, the synthesis of which is induced after inflammation.30 It was been reported the concentration of plasma hemopexin significantly increased at 24 and 48 h following both partial hepatectomy and laparotomy in the rat.31 Haptoglobin is necessary to avoid iron loss during hemolysis, and it reduces the free radical production of serum hemoglobin.32 The mRNAs of haptoglobin in liver were found beginning to elevate after 24 h of PHx in Fulop’s study.32 This correlated with our observation that Hp gradually increased after PHx and had highest level at 48 and 72 h. Except for Hp and Hpx, another acute-phase protein, Apolipoprotein A-IV precursor (Apoa4), was also found upregulated in our study. Apoa4 was reported as increased in the serum during inflammation in mouse HDL.33 It inhibited the lipid peroxidation demonstrated potential antiatherogenic properties and acted as an endogenous anti-inflammatory protein in DSS-induced inflammation mice.34 In our study, Apoa4 highly expressed in the early stages of the regeneration, 24 h, and then gradually decreased when regeneration proceeded further. It may indicate that Apoa4 might act as early response genes to prevent inflammation induced by PHx. Mt1 highly expressed in the beginning of the regeneration, 24 and 48 h, but decreased at 72 h. Although Mt2 was only identified and quantified in one of the experiment, it showed similar expression profiles to Mt1. Mt1 and Mt2 were two of the proteins that were up-regulated at all three time points, especially at 24 and 48 h. It has been reported that MTs are produced in response to a variety of stresses, inflammation, and as components of the acute-phase response and it may play a major role in the prevention of tissue damage.35 In addition, accumulated evidence revealed an essential role of MT in liver cell regeneration. MTs are cysteine-rich zinc (Zn) and copper (Cu) binding proteins with low-molecular-weight and antioxidant properties. The transfer of zinc from MT to various metalloenzymes and transcription factors has been Journal of Proteome Research • Vol. 8, No. 2, 2009 1009
1010
Macrophage migration inhibitory factor Alcohol dehydrogenase 1
Beta-lactamase-like protein 2 Fatty acid binding protein 5, epidermal Isoform 1 of Liver carboxylesterase 31 precursor 3-ketoacyl-CoA thiolase B, peroxisomal precursor similar to Isopentenyldiphosphate delta isomerase
S-adenosylmethionine synthetase isoform type-1
aspartyl aminopeptidase isoform a
poly A binding protein, cytoplasmic 1 apolipoprotein A-IV Ornithine aminotransferase, mitochondrial precursor
Hemopexin precursor
Haptoglobin precursor
Metallothionein-1
IPI00230427
IPI00116221
Journal of Proteome Research • Vol. 8, No. 2, 2009
IPI00128518
IPI00331394
IPI00331552
IPI00128484
IPI00409148
IPI00113696
IPI00775913 IPI00129178
IPI00849448
IPI00122139
IPI00381178
IPI00876563
IPI00221400
Carbonic anhydrase 3
description
IPI00221890
accession number
Mt1
Hp
Hpx
Apoa4 Oat
Pabpc1
Dnpep
Mat1a
LOC100044783
Acaa1b
Es31
Fabp5
Lactb2
Adh1
Mif
Car3
gene name
1.56
6.38
5.06 ( 2.01
1.50
2.28 ( 0.64
2.18 ( 0.55
0.48
0.58 ( 0.11
0.69
0.67
0.68 ( 0.25
1.42 ( 0.18
0.51
0.68 ( 0.05
3.21 1.53
1.10
0.83 ( 0.06
1.92 ( 0.19 1.30 ( 0.08
0.68
0.55 ( 0.14
1.44
1.05
1.05 ( 0.01
1.45 ( 0.61
0.30
0.41 ( 0.03
1.22
0.82
0.90 ( 0.01
1.46
group 2
group 1
24 h/control (ratio ( SD) group 2
5.74 ( 2.76
2.18 ( 0.04
1.59 ( 0.12
2.21 ( 0.02 2.39 ( 0.16
1.71 ( 0.27
5.30
2.28
1.42
1.77 1.86
1.92
4.70
1.08
up-Regulation 1.62 ( 0.06
2.85
1.27
0.54
0.20
0.52
0.80
0.60
0.26
1.13 ( 0.24
0.56 ( 0.23
0.58 ( 0.04
0.63 ( 0.06
0.73 ( 0.19
0.82 ( 0.03
0.60 ( 0.05
down-Regulation 0.56 ( 0.02 0.44
group 1
48 h/control (ratio ( SD)
2.58 ( 096
2.27 ( 0.94
1.94 ( 0.30
1.45 ( 0.04 1.88 ( 0.04
1.11 ( 0.30
1.03
1.10 ( 0.02
0.42 ( 0.13
0.61 ( 0.10
0.71 ( 0.02
0.46 ( 0.01
0.66 ( 0.10
0.61 ( 0.03
0.56 ( 0.02
0.55 ( 0.01
group 1
2.87
2.14
1.97
1.76 1.83
1.34
1.23
1.21
1.04
0.95
0.83
0.68
0.67
0.64
0.47
0.46
group 2
72 h/control (ratio ( SD)
Table 1. A List of 16 Proteins Whose Expressions Were Down- or Up-Regulated by Factor of at Least 1.5 in at Least One Time Point
ATP binding, cobalt ion binding, magnesium ion binding, metal ion binding, methionine adenosyltransferase activity, nucleotide binding, potassium ion binding, transferase activity aminopeptidase activity, aspartyl aminopeptidase activity, hydrolase activity, metal ion binding, metallopeptidase activity, peptidase activity, zinc ion binding RNA binding, nucleic acid binding, nucleotide binding, poly(A) binding lipid binding, lipid transporter activity catalytic activity, ornithine-oxo-acid transaminase activity, pyridoxal phosphate binding, transaminase activity, transferase activity catalytic activity, iron ion binding, metal ion binding chymotrypsin activity, hemoglobin binding, serine-type endopeptidase activity, trypsin activity copper ion binding, metal ion binding, zinc ion binding
acyltransferase activity, transferase activity
carboxylesterase activity, hydrolase activity
carbonate dehydratase activity, lyase activity, metal ion binding, nickel ion binding, zinc ion binding cytokine activity, isomerase activity, phenylpyruvate tautomerase activity alcohol dehydrogenase activity, metal ion binding, oxidoreductase activity, protein homodimerization activity, zinc ion binding hydrolase activity, metal ion binding, zinc ion binding binding, lipid binding, transporter activity
functional ontology
research articles Hsieh et al.
Protein Profilings in Mouse Liver Regeneration
Figure 6. Time-dependent expressional patterns of (a) downregulated and (b) up-regulated proteins. The averaged ratios relative to control were plotted over time. The ratio of control liver was set as 1 and indicated in the 0 h of the plot.
Figure 7. Expressions of Mat1a and Actb, monitored using iTRAQ technology (A) and Western blot analysis (B) in control liver and livers regenerating for 24, 48 and 72 h. Similar to the iTRAQ results, Western blot analysis revealed that Mat1a exhibited the strongest expression at 24 and 48 h and declined at 72 h. The expression of Actb changed little during liver regeneration.
described.36 The regenerating cells require large amounts of zinc within short period of time, and this requirement is met by the induction of a zinc and copper binding protein, metallothionein (Mt), during the priming step, soon after an injury.36,37 It had been demonstrated that Mt levels were increased in WT mice at 24 h after PHx and declined to normal levels by 60 h after PHx.38 The time-dependent expression
research articles profile was consistent with our observation. In the same study, it was also reported that cell proliferation was significantly less in Mt-null mice as compared to wild-type mice during liver regeneration after PH.38 This indicated that Mt was induced after PHx not only for preventing tissue damage, but also involving cell proliferation. In this work, the time-dependent expression profiles of Mt1 and Mt2 correlated well with the rate of regeneration as indicated by liver mass. The observations herein further verified the importance of Mts to liver regeneration. Methionine adenosyltransferase 1A (Mat1a) was up-regulated, especially at 24 h after PHx. Mat1a is an isoform of the methionine adenosyltransferase (Mat) family. Numerous studies have reported that the mRNA level of MAT was up-regulated in liver regeneration after PHx.39-41 Mat1a participates in the activation of the cell proliferation signal transduction pathway with tumor necrosis factor R (TNF-R), nuclear factor kappa B (NFkappaB), c-Jun-N-terminal kinase (Jnk) and extracellular signal-regulated kinases (Erks).39,42 Transforming growth factor beta (TGF-β1) elevated the mRNA level of Mat1a in one investigation,43 supporting the assertion that it may be the upstream genes of the signal transduction pathway in Mat1a, TGF-β1 and TNF cell proliferation networks. In addition to the acute-phase proteins, macrophage migration inhibitory factor (Mif), which is a critical regulating cytokine of the inflammatory pathways,44 was identified in the present study. Lack of Mif had been reported to protect the mice from Con A-induced liver injury.45 It had also been reported that anti-mouse Mif antibody treatment reduced liver injury and protected liver from acute hepatic failure by regulating T-cell infiltration.46,47 In this study, Mif was significantly reduced especially at 24 h after PHx. This result might suggest that Mif was down-regulated to protect liver from further injury after PHx. Although numerous cytokine- and growth-factor-mediated pathways that regulate liver regeneration have been clearly eluicidated,1-3 there are still some proteins that are involved in liver regeneration but not been yet associated with specific pathways.3,48 In our study, we identified several proteins which may play important roles in liver regeneration and had not been elucidated before. Alcohol dehydrogenase (Adh1) was down-regulated at late stages of regeneration. Adh1 is required for oxidizing of excess retinol to retinoic acid (RA).49 Retinol, also known as Vitamin A, is a nutrient that is essential for developmental regulation but toxic in large amounts. It has been demonstrated that the administration of vitamin A to the vitamin-A-deficient animals enhanced the capacity of the liver to regenerate by preventing apoptosis and necrotic cell death.50 It has also been reported that RA exerts the antiproliferative activity in the early stage of liver regeneration accompanied by the repression of c-fos and c-jun expression and induction of apoptosis.51 Adh1 was found slowly decreasing after PHx in our study. This result might suggest that the Adh1 was downregulated to prevent apoptosis by increasing retinol level during liver regeneration. This also supported the hypothesis made by Lo´pez-Valencia et al. that PH-induced inhibition of Adh (mainly type I) seems to be related to Adh-mediated retinoid metabolism during liver proliferation.52 Various investigations of mouse liver regeneration after a partial hepatectomy have been conducted.1,23,25,51 Most of these works were based primarily on 2D-PAGE-based strategy. We believe that this is the first study to exploit the iTRAQ proteomic technique to profile the time-dependent protein changes in liver regeneration. Several proteins showed difJournal of Proteome Research • Vol. 8, No. 2, 2009 1011
research articles ferential expression during liver regeneration after PHx. Many of them have been reportedly involved in liver regeneration. However, the roles which other differentially expressed proteins play in liver regeneration are still unclear. More work must be conducted in this area to elucidate further the mechanism and functionality of liver regeneration. In conclusion, this work demonstrates that the iTRAQ technique not only is effective for studying liver regeneration, but also provides results that are consistent with those presented elsewhere. Abbreviations: 2-D PAGE, two-dimensional polyacrylamide gel electrophoresis; CV, coefficient of variation; DIGE, difference gel electrophoresis; Erks, extracellular signal-regulated kinases; ICAT, isotope-coded affinity tags; iTRAQ, isobaric tags for relative and absolute quantitation; Idi1, isopentenyl-diphosphate delta isomerase; Jnk, c-Jun-N-terminal kinase; Mt, metallothionein; Mt2, metallothionein 2; NF-kappaB, nuclear factor kappaB; PHx, partial hepatectomy; PVDF, polyvinylidene difluoride; SCX, strong cation exchange; SELDI-TOF MS, surfaceenhanced laser desorption ionization-time-of-flight mass spectrometry; SILAC, stable isotope labeling with amino acids in cell culture; TGF-R, transforming growth factor alpha; TGFβ1, transforming growth factor beta 1; TNF, tumor necrosis factor; TNF-R, tumor necrosis factor R.
Supporting Information Available: Supplementary tables 1 and 2 listed peptides identified, sequence coverage, protein identification probability from Mascot search engine. Supplementary table 3 listed the quantitative results of 270 proteins quantified in both biological groups. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Fausto, N. Liver regeneration. J. Hepatol. 2000, 32, 19–31. (2) Michalopoulos, G. K.; DeFrances, M. C. Liver regeneration. Science 1997, 276, 60–66. (3) Taub, R. Liver regeneration: from myth to mechanism. Nat. Rev. Mol. Cell. Biol. 2004, 5, 836–847. (4) Webber, E. M.; Bruix, J.; Pierce, R. H.; Fausto, N. Tumor necrosis factor primes hepatocytes for DNA replication in the rat. Hepatology 1998, 28, 1226–1234. (5) O’Farrell, P. H. High resolution two-dimensional electrophoresis of proteins. J. Biol. Chem. 1975, 250, 4007–4021. (6) Klose, J.; Kobalz, U. Two-dimensional electrophoresis of proteins: an updated protocol and implications for a functional analysis of the genome. Electrophoresis 1995, 16, 1034–1059. (7) Righetti, P. G.; Castagna, A.; Antonucci, F.; Piubelli, C.; Cecconi, D.; Campostrini, N.; Antonioli, P.; Astner, H.; Hamdan, M. Critical survey of quantitative proteomics in two-dimensional electrophoretic approaches. J. Chromatogr., A 2004, 1051, 3–17. (8) Unlu, M.; Morgan, M. E.; Minden, J. S. Difference gel electrophoresis: a single gel method for detecting changes in protein extracts. Electrophoresis 1997, 18, 2071–2077. (9) Tonge, R.; Shaw, J.; Middleton, B.; Rowlinson, R.; Rayner, S.; Young, J.; Pognan, F.; Hawkins, E.; Currie, I.; Davison, M. Validation and development of fluorescence two-dimensional differential gel electrophoresis proteomics technology. Proteomics 2001, 1, 377– 396. (10) Bondarenko, P. V.; Chelius, D.; Shaler, T. A. Identification and relative quantitation of protein mixtures by enzymatic digestion followed by capillary reversed-phase liquid chromatographytandem mass spectrometry. Anal. Chem. 2002, 74 (18), 4741–4749. (11) Ono, M.; Shitashige, M.; Honda, K.; Isobe, T; Kuwabara, H.; Matsuzuki, H.; Hirohashi, S; Yamada, T. Label-free quantitative proteomics using large peptide data sets generated by nanoflow liquid chromatography and mass spectrometry. Mol. Cell. Proteomics. 2006, 5 (7), 1338–1347. (12) Wang, G.; Wu, W. W.; Zeng, W.; Chou, C.-L.; Shen, R.-F. Labelfree protein quantification using LC-coupled ion trap or FT mass spectrometry: Reproducibility, linearity, and application with complex proteomes. J. Proteome Res. 2006, 5 (5), 1214–1223. (13) Ong, S. E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D. B.; Steen, H.; Pandey, A.; Mann, M. Stable isotope labeling by amino acids
1012
Journal of Proteome Research • Vol. 8, No. 2, 2009
Hsieh et al.
(14) (15)
(16)
(17)
(18)
(19)
(20)
(21)
(22) (23) (24)
(25) (26) (27) (28)
(29)
(30) (31) (32)
(33)
(34)
in cell culture, SILAC, as a simple and accurate approach to expression proteomics.\. Mol. Cell. Proteomics 2002, 1, 376–386. Ong, S. E.; Foster, L. J.; Mann, M. Mass spectrometric-based approaches in quantitative proteomics. Methods 2003, 29, 124– 130. Gygi, S. P.; Rist, B.; Gerber, S. A.; Turecek, F.; Gelb, M. H.; Aebersold, R. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat. Biotechnol. 1999, 17, 994– 999. Han, D. K.; Eng, J.; Zhou, H.; Aebersold, R. Quantitative profiling of differentiation-induced microsomal proteins using isotopecoded affinity tags and mass spectrometry. Nat. Biotechnol. 2001, 19, 946–951. Wu, W. W.; Wang, G.; Baek, S. J.; Shen, R. F. Comparative study of three proteomic quantitative methods, DIGE, cICAT, and iTRAQ, using 2D gel- or LC-MALDI TOF/TOF. J. Proteome Res. 2006, 5, 651–658. Cong, Y. S.; Fan, E.; Wang, E. Simultaneous proteomic profiling of four different growth states of human fibroblasts, using aminereactive isobaric tagging reagents and tandem mass spectrometry. Mech. Ageing Dev. 2006, 127, 332–343. Chen, X.; Walker, A. K.; Strahler, J. R.; Simon, E. S.; TomanicekVolk, S. L.; Nelson, B. B.; Hurley, M. C.; Ernst, S. A.; Williams, J. A.; Andrews, P. C. Organellar proteomics: analysis of pancreatic zymogen granule membranes. Mol. Cell. Proteomics 2006, 5, 306– 312. DeSouza, L.; Diehl, G.; Rodrigues, M. J.; Guo, J.; Romaschin, A. D.; Colgan, T. J.; Siu, K. W. Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and cICAT with multidimensional liquid chromatography and tandem mass spectrometry. J. Proteome Res. 2005, 4, 377–386. Ross, P. L.; Huang, Y. N.; Marchese, J. N.; Williamson, B.; Parker, K.; Hattan, S.; Khainovski, N.; Pillai, S.; Dey, S.; Daniels, S.; Purkayastha, S.; Juhasz, P.; Martin, S.; Bartlet-Jones, M.; He, F.; Jacobson, A.; Pappin, D. J. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell. Proteomics 2004, 3, 1154–1169. Pahlavan, P. S.; Feldmann, R. E., Jr; Zavos, C.; Kountouras, J. Prometheus’ challenge: molecular, cellular and systemic aspects of liver regeneration. J. Surg. Res. 2006, 134, 238–251. Sun, Y.; Deng, X.; Li, W.; Yan, Y.; Wei, H.; Jiang, Y.; He, F. Liver proteome analysis of adaptive response in rat immediately after partial hepatectomy. Proteomics 2007, 7, 4398–407. Guo, F.; Nian, H.; Zhang, H.; Huang, L.; Tang, Y.; Xiao, X.; He, D. Proteomic analysis of the transition from quiescent to proliferating stages in rat liver hepatectomy model. Proteomics 2006, 6, 3075– 3086. Strey, C. W.; Winters, M. S.; Markiewski, M. M.; Lambris, J. D. Partial hepatectomy induced liver proteome changes in mice. Proteomics 2005, 5, 318–325. Sun, Q.; Miao, M.; Jia, X.; Guo, W.; Wang, L.; Yao, Z.; Liu, C.; Jiao, B. Subproteomic analysis of the mitochondrial proteins in rats 24 h after partial hepatectomy. J. Cell Biochem. 2008, 105, 176–184. Bowman, B. H.; Kurosky, A. Haptoglobin: the evolutionary product of duplication, unequal crossing over, and point mutation. Adv. Hum. Genet. 1982, 12, 453–454. Altruda, F.; Poli, V.; Restagno, G.; Argos, P.; Cortese, R.; Silengo, L. The primary structure of human hemopexin deduced from cDNA sequence: evidence for internal, repeating homology. Nucleic Acids Res. 1985, 13, 3841–3859. Tolosano, E.; Fagoonee, S.; Hirsch, E.; Berger, F. G.; Baumann, H.; Silengo, L.; Altruda, F. Enhanced splenomegaly and severe liver inflammation in haptoglobin/hemopexin double-null mice after acute hemolysis. Blood. 2002, 100, 4201–4208. Tolosano, E.; Altruda, F. Hemopexin: structure, function, and regulation. DNA Cell Biol. 2002, 21, 297–306. Murray-Lyon, I. M.; Liem, H. H.; Muller-Eberhard, U. Synthesis of plasma haemopexin, albumin and fibrinogen by the regenerating rat liver. Br. J. Exp. Pathol. 1975, 56, 247–255. Fulop, A. K.; Pocsik, E.; Brozik, M.; Karabelyos, C.; Kiss, A.; Novak, I.; Szalai, C.; Dobozy, O.; Falus, A. Hepatic regeneration induces transient acute phase reaction: systemic elevation of acute phase reactants and soluble cytokine receptors. Cell Biol Int. 2001, 25, 585–592. Khovidhunkit, W.; Duchateau, P. N.; Medzihradszky, K. F.; Moser, A. H.; Naya-Vigne, J.; Shigenaga, J. K.; Kane, J. P.; Grunfeld, C.; Feingold, K. R. Apolipoproteins A-IV and A-V are acute-phase proteins in mouse HDL. Atherosclerosis. 2004, 176, 37–44. Vowinkel, T.; Mori, M.; Krieglstein, C. F.; Russell, J.; Saijo, F.; Bharwani, S.; Turnage, R. H.; Davidson, W. S.; Tso, P.; Granger,
research articles
Protein Profilings in Mouse Liver Regeneration
(35) (36) (37)
(38)
(39)
(40) (41) (42) (43) (44) (45)
D. N.; Kalogeris, T. J. Apolipoprotein A-IV inhibits experimental colitis. J. Clin. Invest. 2004, 114, 260–269. Manuel, Y.; Thomas, Y.; Pellegrini, O. Metallothionein and tissue damage. IARC Sci. Publ. 1992, 118, 231–237. Cherian, M. G.; Kang, Y. J. Metallothionein and liver cell regeneration. Exp. Biol. Med. (Maywood, NJ, U.S.). 2006, 231, 138–144. Oliver, J. R.; Jiang, S.; Cherian, M. G. Augmented hepatic injury followed by impaired regeneration in metallothionein-I/II knockout mice after treatment with thioacetamide. Toxicol. Appl. Pharmacol. 2006, 210, 190–199. Oliver, J. R.; Mara, T. W.; Cherian, M. G. Impaired hepatic regeneration in metallothionein-I/II knockout mice after partial hepatectomy. Exp. Biol. Med. (Maywood, NJ, U.S.). 2005, 230, 61– 67. Horikawa, S.; Ozasa, H.; Ito, K.; Katsuyama, I.; Tsukada, K.; Sugiyama, T. Expression of S-adenosylmethionine synthetase isozyme genes in regenerating rat liver after partial hepatectomy. Biochem. Mol. Biol. Int. 1996, 40, 807–814. Frago, L. M.; Gimenez, A.; Rodriguez, E. N.; Varela-Nieto, I. Shortchain ceramide regulates hepatic methionine adenosyltransferase expression. FEBS Lett. 1998, 426, 305–308. Huang, Z. Z.; Mao, Z.; Cai, J.; Lu, S. C. Changes in methionine adenosyltransferase during liver regeneration in the rat. Am. J. Physiol. 1998, 275, G14–21. Fausto, N.; Campbell, J. S.; Riehle, K. J. Liver regeneration. Hepatology 2006, 43, S45–53. Lin, W. C.; Lin, W. L. Ameliorative effect of Ganoderma lucidum on carbon tetrachloride-induced liver fibrosis in rats. World J. Gastroenterol. 2006, 12 (2), 265–270. Larson, D. F.; Horak, K. Macrophage migration inhibitory factor: controller of systemic inflammation. Crit Care. 2006, 10, 138. Nakajima, H.; Takagi, H.; Horiguchi, N.; Toyoda, M.; Kanda, D.; Otsuka, T.; Emoto, Y.; Emoto, M.; Mori, M. Lack of macrophage
(46)
(47)
(48)
(49)
(50)
(51)
(52)
migration inhibitory factor protects mice against concanavalin A-induced liver injury. Liver Int. 2006, 26, 346–351. Kimura, K.; Nagaki, M.; Nishihira, J.; Satake, S.; Kuwata, K.; Moriwaki, H. Role of macrophage migration inhibitory factor in hepatitis B virus-specific cytotoxic-T-lymphocyte-induced liver injury. Clin. Vaccine Immunol. 2006, 13, 415–419. Kobayashi, S.; Nishihira, J.; Watanabe, S.; Todo, S. Prevention of lethal acute hepatic failure by antimacrophage migration inhibitory factor antibody in mice treated with bacille Calmette-Guerin and lipopolysaccharide. Hepatology 1999, 29, 1752–1759. Costa, R. H.; Kalinichenko, V. V.; Holterman, A. X.; Wang, X. Transcription factors in liver development, differentiation, and regeneration. Hepatology. 2003, 38, 1331–1347. Molotkov, A.; Duester, G. Genetic evidence that retinaldehyde dehydrogenase Raldh1 (Aldh1a1) functions downstream of alcohol dehydrogenase Adh1 in metabolism of retinol to retinoic acid. J. Biol. Chem. 2003, 278, 36085–36090. Evarts, R. P.; Hu, Z.; Omori, N.; Omori, M.; Marsden, E. R.; Thorgeirsson, S. S. Effect of vitamin A deficiency on the integrity of hepatocytes after partial hepatectomy. Am. J. Pathol. 1995, 147, 699–706. Ozeki, A.; Tsukamoto, I. Retinoic acid repressed the expression of c-fos and c-jun and induced apoptosis in regenerating rat liver after partial hepatectomy. Biochim. Biophys. Acta. 1999, 1450, 308– 319. Lo´pez-Valencia, V.; Rangel, P.; Rodrı´guez, S.; Herna´ndez-Mun ˜ oz, R. Involvement of alcohol and aldehyde dehydrogenase activities on hepatic retinoid metabolism and its possible participation in the progression of rat liver regeneration. Biochem. Pharmacol. 2007, 73, 586–596.
PR800696M
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