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J. Biol. Chem., Vol. 278, Issue 32, 29813-29818, August 8, 2003
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¶
From the
Departments of Medicine and Clinical
Oncology, Functional Genomics, and
Biochemistry and Genetics, Graduate School
of Medicine, Chiba University, Chiba 260-8670, Japan, the
||Department of Life Science Products, Hitachi
Software Engineering Co., Ltd., Yokohama, 230-0045, Japan, and
**Department of Virology, Institute of Medical
Sciences, University of Tokyo, Minato-ku, Tokyo 108-8639, Japan, and the
Division of Genetic Resources,
National Institute of Infectious Diseases, Shinjuku-ku, Tokyo 162-8640,
Japan
Received for publication, December 11, 2002 , and in revised form, May 12, 2003.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONEXPERIMENTAL PROCEDURESRESULTS AND DISCUSSIONREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONEXPERIMENTAL PROCEDURESRESULTS AND DISCUSSIONREFERENCES |
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, hormones and growth factors including insulin, norepinephrine,
hepatocyte growth factor, and epidermal growth factor, and a number of
transcription factors have been shown to be involved in liver regeneration
(1–3).
While administration of these proteins and/or overexpression of their genes
induced the rapid regeneration, disruption of the genes in mice resulted in
severe impairment of the regeneration
(1–3).
Despite the clarification of the importance of these genes for liver
regeneration, the complex mechanism for the regeneration by the interplay of
many factors remains to be investigated. The expression patterns of many genes associated with liver regeneration were discussed previously (4). However, a simultaneous and comprehensive analysis of the expression profiles of these genes has been difficult because of technical limitation. Recently, DNA microarray technology has been developed and shown to be a powerful tool for analyzing the expression profiles of many genes at one time (5). By using this technique, Su et al. (6) revealed gene expression profiles during the priming phase of liver regeneration up to 4 h after partial hepatectomy (PHx),1 and demonstrated the changes in expression of 185 genes. After the priming phase, hepatocytes proliferation starts at the periportal area of the lobular architecture and then proceeds to the perivenular areas (1, 7). Since the peaks of DNA synthesis in hepatocytes after PHx are around 24–40 h (1, 3), here we analyzed the changes in gene expression up to 48 h by using an in-house microarray harboring mouse liver cDNAs. 317 genes were shown to be up- or down-regulated during the course following PHx, and their clustering analysis revealed striking features of expression profiles of functionally classified genes, giving insights into roles and regulation of genes in liver regeneration.
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EXPERIMENTAL PROCEDURES |
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TOPABSTRACTINTRODUCTIONEXPERIMENTAL PROCEDURESRESULTS AND DISCUSSIONREFERENCES |
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Preparation of the cDNA Microarray—A cDNA microarray chip, consisting of 2,304 cDNA (1,504 known genes and 800 unknown genes) was made as described previously (5, 9, 10). 2,304 unique clones were selected from about 9,000 sequenced clones in an oligo-capped cDNA library (11) of the mouse liver. PCR-amplified cDNA products were mixed with nitrocellulose in dimethyl sulfoxide and then spotted onto carbodiimide-coated glass slides using robotics SPBIO-2000 (Hitachi Software Engineering Co., Yokohama, Japan).
Microarray Analysis—Fluorescent cDNA probes (Cy3- or Cy5-labeled) were prepared from 2 µg of poly(A)+ RNA. Hybridization and fluorescence detection were performed essentially as described previously (9). Images were analyzed with Quant Array (GSI Lumonics, Nepean, Canada) and DNASIS Array (Hitachi Software Engineering) according to the manufacturer's instructions. The intensities of four areas between diagonal spots were used as the background for each spot. The mean and S.D. of background levels were calculated, and the genes whose intensities were less than mean plus 2 S.D. of background levels at any of the time points were excluded from further analysis. The Cy5/Cy3 ratios of all spots on the microarray were normalized by dividing them by the median. Averaged data of the two animals were subjected to statistical analysis.
Northern Blot Analysis—20 µg of total RNA were
electrophoresed through a 1% agarose-formaldehyde gel, transferred to a
nitrocellulose membrane (Amersham Biosciences) overnight and cross-linked with
irradiation. Probes were generated using Megaprime DNA labeling system
(Amersham Biosciences) and [-32P]dCTP. Probes and blots were
hybridized in Rapid-Hyb buffer (Amersham Biosciences). Experiments were
performed twice and quantified using BAS 2000 (Fuji Photo Film Co., Tokyo,
Japan).
Statistical Analysis and Annotation of Gene Function—The normalized Cy5/Cy3 ratios in the microarray analysis were log2-transrformed and used to classify the patterns of serial changes of the gene expression. Genes whose expression levels varied at least 2-fold or by 2 S.D. at any of the time points were subjected to hierarchical clustering analysis, using the algorithm of Euclid and Ward in GeneMaths software (Applied Maths BVBA, Sint-Martens-Latem, Belgium).
The molecular functions of the genes were assigned referring to GENE ONTOLOGYTM (www.geneontology.org/) and GeneCardsTM (bioinfo.weizmann.ac.il/cards/).
To examine statistical significance for frequencies of genes of each functional group in each cluster, values of the other groups in the relevant cluster, and values of the other clusters in the relevant group, were each combined, and the resultant combined values were compared with the relevant value with Fisher's exact test by computing for the 2 x 2 table with the statistical program StatView (SAS Institute Inc., Cary, NC).
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONEXPERIMENTAL PROCEDURESRESULTS AND DISCUSSIONREFERENCES |
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To determine the validity of results obtained by the microarray analysis,
10 randomly selected genes were subjected to Northern blot analysis. While
mRNAs for two genes (glutathione peroxidase and itih-4) were under
the detectable level in Northern analysis (data not shown), mRNA levels of the
other eight genes (S-adenosylmethionine synthetase, claudin-1,
squalene synthase, virus-like retro-element, leptin receptor, insulin-like
growth factor-binding protein 1, haptoglobin, and -1 acid glycoprotein
1B) were almost comparable between microarray and Northern analysis
(Fig. 1), generally verifying
the competency of the microarray analysis for detection of changes in gene
expression after PHx. However, some discrepancy was present between the
results of microarray and Northern experiments. Following analyses on
microarray data were done with gene numbers large enough for statistical
treatment.
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Serial Changes in Expression Levels of the Genes in Relation to Their Functions—The 317 genes with the changes in their expression levels after PHx were subjected to clustering analysis based on expression patterns and were classified into eight clusters (Table SI (see Supplemental Material) and Fig. 2A). Time course of changes in mRNA levels in each cluster can be roughly characterized as follows (Fig. 2B): cluster A, rapid increase and persistence; cluster B, transient up-regulation and gradual decrease; cluster C, gradual increase; cluster D, transient down-regulation and rebound; cluster E, rapid increase and rapid return; cluster F, transient down-regulation and gradual increase; cluster G, general decrease; cluster H, transient down-regulation and persistence.
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We also categorized the 317 genes based on their functions, referring to GENE ONTOLOGYTM and GeneCardsTM, and classified them into 11 groups (Table SI in Supplemental Material and Fig. 3): cell growth and maintenance, cytoskeleton and cell membrane, metabolism, secreted proteins, signal transduction, transcription and processing, translation and processing, mitochondrion, others, and expressed sequence tags (EST). Frequencies of these functionally classified genes in each cluster are shown in Fig. 3, with statistical significance evaluated by Fisher's exact test for high and low frequencies.
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Hitherto, we have used the 2-/0.5-fold changes in expression levels as cut-off values for seemingly reliable changes, which were exhibited by 17, 29, 23, 23, and 15% (amounting to 317 genes in total) of intensity-measurable 496 genes at the time points of 2, 6, 12, 24, and 48 h, respectively. The 2-/0.5-fold changes corresponded with 1.41/-1.12, 1.51/-0.75, 1.24/-0.97, 1.12/-1.34, and 1.21/-1.32 S.D. at each time point. We also tested a more stringent cut-off value of ±2 S.D., to verify the cluster-function relationship (Fig. 4). The numbers of genes that exceeded this cut-off value occupied 3.8, 4.8, 5.6, 3.2, and 5.0% (amounting to 68 genes in total) of the 496 genes at each time point. The 68 genes were classified into five clusters (a–e) by hierarchical clustering analysis. Their features are as follows: cluster a, rapid increase and rapid return; cluster b, rapid increase and persistence; cluster c, transient up-regulation and gradual decrease; cluster d, gradual increase; cluster e, general decrease. Again, frequencies of functionally categorized genes in these clusters are represented with their statistical significance (Fig. 4, right panels). Together with the results of Fig. 3, high frequencies were reproducibly observed in following gene distributions: genes for the category "translation and processing" in the cluster "rapid increase and persistence" (clusters A and b in Figs. 3 and 4, respectively); "secreted proteins" in "gradual increase" (clusters C and F and d); "metabolism" in "general decrease" (clusters G and e). We will discuss these characteristic gene distributions below, mainly based on the gene cluster classification in Table SI in Supplemental Material and Figs. 2 and 3.
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Activation of Genes in the Category "Translation and Processing" in the Early Stage of Liver Regeneration—Among genes in the cluster A with properties of rapid activation and following persistence, significantly frequent were members of the category "translation and processing" (Fig. 3), which are a ribosomal protein (number 19 in Table SI in Supplemental Material), elongation factors (numbers 16 and 17 in Table SI in Supplemental Material) and components of protein transport machineries (numbers 1 and 24 in Table SI in Supplemental Material). This suggests that machinery for protein synthesis, folding, and transport were prepared at the early stage of liver regeneration, presumably to synthesize and deliver proteins of altered population with modified efficiencies. Importance of adequate protein synthesis and processing for cells to pass the restriction point and enter the S phase has been repeatedly noted. When the cellular ribosome content decreases, the translation of CLN3 mRNA is inhibited, presumably leading to growth arrest (12). Involvement of translation factors in growth regulation has been most dramatically exemplified by the fact that overexpression of the mRNA cap binding protein (eIF4E) causes deregulated cell growth and malignant transformation of rodent and human cells (13). Importance of cotranslational and posttranslational protein quality control in cell cycle progression has been also stressed. For example, accumulation of misfolded proteins in endoplasmic reticulum inhibits cyclin D1 translation and results in cell cycle arrest (14). After PHx, most of the hepatocytes in the residual liver should participate in one or two proliferative events theoretically, and the peak of DNA synthesis is about at 24–40 h (1, 3). Most of hepatocytes have to pass the restriction point and enter the S phase before this period, apparently being reflected by early activation of genes for protein-supplying machineries.
Differential Regulation of Genes for Categories "Metabolism" and "Secreted Proteins"—Genes for two major live functions, i.e. intermediary metabolism and plasma protein secretion exhibited distinctive cluster assignment. The category "metabolism" is mainly composed of enzymes involved in hepatic intermediary metabolism of compounds such as sugars, lipids, amino acids, nucleotides, steroids, and xenobiotics. Genes of this category were significantly enriched in the cluster G, which exhibited general features of gene repression: a majority of mRNAs were under the control level even at 24 and 48 h after PHx (Fig. 2B). Seemingly, metabolic enzymes in the liver have catalytic capacities sufficient to compensate a two-thirds loss of the liver by PHx, presumably being aided also by prolongation of half-lives of the enzyme proteins during the regeneration. In fact, the degradation rate of protein decreases in the regenerating liver (15).
On the other hand, the category "secreted proteins" contains
plasma proteins as a large majority and a small number of proteins involved in
local liver function. Genes of this category were enriched in the clusters C
and F, which are characterized by gradual increases in mRNA levels despite
down-regulation, if any, in the early periods. Most of mRNAs were above the
control level at 24 and 48 h following PHx
(Fig. 2B). This may
reflect at least two aspects in regulation of plasma protein levels. One is
induction of acute phase proteins such as fibrinogen subunits (numbers 53 and
65 in Table SI in Supplemental Material), -1 acid glycoprotein 1B
(number 70 in Table SI in Supplemental Material), C-reactive protein (number
137 in Table SI in Supplemental Material) and complement components (number
151 in Table SI in Supplemental Material), in response to systemic injury
following PHx. The other is supplementation of constitutive plasma proteins
that are under constant turnover: the two-thirds PHx seems to impose
upregulation of plasma protein synthesis on the one-third remnant liver.
Thus, syntheses of hepatic enzymes and plasma proteins seem to be regulated in the opposite direction. Amino acids and energy saved by decreased synthesis of enzyme proteins are likely to be turned toward plasma protein synthesis during liver regeneration.
Remarkable Genes with Altered Expression Levels during Liver
Regeneration—Claudin-1 (number 66 in Table SI in Supplemental
Material) in the cluster C is an integral membrane protein of tight junctions
(16). Previously, a related
factor claudin-3 was reported to be up-regulated during liver regeneration
(17). Behavior of tight
junctions during cell division is potentially very interesting. 55.11 binding
protein (number 63 in Table SI in Supplemental Material, also designated
TRAP2) in the cluster C is a regulatory component of the 26S proteasome and
binds to the p55 tumor necrosis factor receptor
(18), possibly allowing direct
regulation of the proteasome by the receptor
(19). Heat shock protein (Hsp)
84-1 (number 64 in Table SI in Supplemental Material, also designated Hsp84
and Hsp90) in the cluster C was previously shown to be induced during liver
regeneration (20), and was
recently reported to participate also in tumor necrosis factor-induced
activation of I
B kinase
(21). Hepatocyte nuclear
factor (HNF)-3
(number 116 in Table SI in Supplemental Material, also
designated Foxa2) was among the four members of the cluster E, which exhibited
a striking expression profile of rapid transient augmentation. HNF-3,
-3, and -3
are members of the winged helix/fork head
transcription factor family and regulate a number of hepatocyte-specific genes
(22,
23). Another related member
HNF-3/fork head homolog (HFH)-11B (Foxm1) was shown to be
up-regulated during the regeneration
(24). In
HFH-11B-overexpressing transgenic mice, the onset of hepatocyte DNA
replication and mitosis during liver regeneration was accelerated
(25). Thus, the winged
helix/fork head transcription factor family including HNF-3
seems to play important roles in liver regeneration. Quiescin Q6 (number 153
in Table SI in Supplemental Material) in the cluster F was originally
identified as a protein strongly induced when fibroblasts enter reversible
quiescence, suggesting a role in growth regulation
(26). Recently, this protein
was shown to be a sulfhydryl oxidase that catalyzes formation of disulfide
bonds in reduced proteins
(27). Quiescin Q6 was detected
in the endoplasmic reticulum and Golgi apparatus as well as outside the cell
and seems to be involved in oxidative folding of various proteins including
secreted ones (26).
Consistently, Quiescin Q6 resides in the cluster F that harbors a number of
secreted proteins, the candidate substrates of the enzyme. The observation
that mRNA level of Quiescin Q6 is still increasing at 48 h after PHx (Table SI
in Supplemental Material) is also concordant with the notion that this enzyme
might play a role in growth arrest of the regenerating liver, and it remains
to be investigated.
In conclusion, the present comprehensive study with cDNA microarray analysis and following statistical analysis revealed remarkable features of changes in gene expression during liver regeneration after PHx. It is plausible that early activation of genes for protein synthesis and processing is essential for hepatocytes to enter the S phase. Prolonged activation of plasma protein genes and repression of metabolic enzyme genes suggest dynamic changes in the flow of amino acids and energy in protein synthesis. A number of remarkable individual genes were also identified. These results shed light on mechanism and pathophysiology of the liver regeneration.
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FOOTNOTES |
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The on-line version of the article (available at
http://www.jbc.org)
contains supplemental Table SI.
¶ To whom correspondence should be addressed: Dept. of Medicine and Clinical Oncology (K1), Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chiba 260-8670, Japan. Tel.: 81-43-226-2083; Fax: 81-43-226-2088; E-mail: yokosuka{at}med.m.chiba-u.ac.jp.
1 The abbreviations used are: PHx, partial hepatectomy; Hsp, heat-shock
protein; HNF, hepatocyte nuclear factor; HFH, HNF-3/fork head
homolog.
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ACKNOWLEDGMENTS |
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REFERENCES |
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TOPABSTRACTINTRODUCTIONEXPERIMENTAL PROCEDURESRESULTS AND DISCUSSIONREFERENCES |
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