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World Journal of Gastroenterology logoLink to World Journal of Gastroenterology
. 2006 Aug 21;12(31):4986–4995. doi: 10.3748/wjg.v12.i31.4986

Gene expression analysis of primary normal human hepatocytes infected with human hepatitis B virus

Hyun Mi Ryu 1,2,3,4, Sung Gyoo Park 1,2,3,4, Sung Su Yea 1,2,3,4, Won Hee Jang 1,2,3,4, Young-Il Yang 1,2,3,4, Guhung Jung 1,2,3,4
PMCID: PMC4087401  PMID: 16937494

Abstract

AIM: To find the relationship between hepatitis B virus (HBV) and hepatocytes during the initial state of infection by cDNA microarray.

METHODS: Primary normal human hepatocytes (PNHHs) were isolated and infected with HBV. From the PNHHs, RNA was isolated and inverted into complement DNA (cDNA) with Cy3- or Cy5- labeled dUTP for microarray analysis. The labeled cDNA was hybridized with microarray chip, including 4224 cDNAs. From the image of the microarray, expression profiles were produced and some of them were confirmed by RT-PCR, immunoblot analysis, and NF-κB luciferase reporter assay.

RESULTS: From the cDNA microarray, we obtained 98 differentially regulated genes. Of the 98 genes, 53 were up regulated and 45 down regulated. Interestingly, in the up regulated genes, we found the TNF signaling pathway-related genes: LT-α, TRAF2, and NIK. By using RT-PCR, we confirmed the up-regulation of these genes in HepG2, Huh7, and Chang liver cells, which were transfected with pHBV1.2×, a plasmid encoding all HBV messages. Moreover, these three genes participated in HBV-mediated NF-κB activation.

CONCLUSION: During the initial state of HBV infection, hepatocytes facilitate the activation of NF-κB through up regulation of LT-α, TRAF2, and NIK.

Keywords: cDNA microarray, Primary normal human hepatocytes, LT-α, TRAF2, NIK, NF-κB

INTRODUCTION

Human hepatitis B virus (HBV) is a causative agent for liver diseases such as cirrhosis and hepatocellular carcinoma (HCC)[1]. Chronic infection of HBV affects approximately 800 million people and is the principal cause of chronic liver diseases[2]. Moreover, HBV carriers have a much higher frequency of developing liver cancer than uninfected people[3].

HBV has a small, partially double-stranded DNA genome. After viral infection of hepatocytes, the partially double-stranded DNA genome converts into covalently closed circular DNA (cccDNA) in nuclei[4-7]. Several kinds of viral transcripts are then produced by the host RNA polymerase. The transcripts encode for viral polymerase, viral oncogene HBx protein, and viral structural proteins such as surface proteins and core proteins[3].

Many efforts have been made to investigate the process of liver disease by HBV. Traditional techniques such as Northern blot and reverse transcription polymerase chain reaction (RT-PCR) for identification of genes differentially expressed by HBV infection have shown limited success, because only one gene or at best a handful of genes can be studied in one experiment. However, complementary DNA (cDNA) microarray allows the study of several thousands of genes at one time. To evaluate the relationship between HBV infection and liver diseases, recent studies have analyzed the gene expression profiles at tissue level. In these studies, the effects of HBV infection are analyzed by cDNA microarray analysis of HCC tissue samples[8-10]. Through the analyses, many differentially expressed genes can be identified[11]. The analyses, however, have mainly focused on the gene expression profiles of already transformed cells or long-term infected HBV hepatocytes. Therefore, these analyses mostly stem from the analysis of the end result of pathogenesis of HBV in hepatocytes rather than the analysis of ongoing pathogenesis of HBV infection in hepatocytes. In this report, however, we focused on the gene expression profile analysis of the early stage HBV infection, thereby excluding factors such as responses to host immune surveillance. To mimic the early stage HBV infection of hepatocytes, we isolated primary normal human hepatocytes (PNHHs) and the cells were infected with HBV in culture. These conditions were chosen as they could represent the most similar conditions to those in vivo, except for the absence of other types of cells such as immunocytes. Therefore, gene expression profiles in this report could show the result of interaction only between HBV and PNHHs. In this study we have identified 45 down-regulated genes and 53 up-regulated genes.

MATERIALS AND METHODS

Construction

pHBV1.2×, a plasmid which provides all HBV transcripts, was used to infect PNHHs as previously described[12]. This construct was similar to that as described by Guidotti et al[13]. Mammalian expression vector for NIK and NIK DN (aa 624-947) was provided by DV Goeddel (Turarik Inc.)[14], for TRAF2 and TRAF2 DN (aa 241-501) by Dr. SY Lee[15].

HBV production and infection

We transfected HepG2 cells with pHBV1.2× constructs for generation of HBV using Fugene 6 transfection reagent (Roche) as instructed by the manufacturer. After transfection, the cells were cultured for 5 d and harvested. HBV particles in the harvested media were cleared and concentrated through ultracentrifugation using PST55Ti rotor (Hitachi) for 1 h at 220 000 g with 3 mL cushion buffer containing 20 g/L sucrose, 50 mmol/L Tris-HCl pH 7.5, and 30 mmol/L NaCl. After ultracentrifugation, the pellet was resuspended with 1 × PBS. The resuspended viral solution was filtered with a 0.2 μm pore filter (Millipore). The titer of HBV solution was adjusted to 109 virus genome equivalent (v.g.e.) per mL. PNHHs were infected with the above virus solution at about 100 v.g.e. per cell. Using this method, the efficiency of HBV infection to PNHHs was generally 50%[16].

Isolation and culture of PNHHs

Healthy parts of a liver from a patient who underwent hepatic resection for an intrahepatic stone at the Inje University Paik Hospital, Pusan, Korea was obtained and used as the source of hepatocytes. The removed tissue was immediately placed in Hank’s balanced salt solution (HBSS) and processed for cell culture. Isolation of hepatocytes was performed using a two-step collagenase perfusion technique[17,18]. The isolated hepatocytes were resuspended in a nutrient medium containing 90 mL/L Williams’ E and 10 mL/L Medium 199, supplemented with 10 μg/mL insulin, 5 μg/mL transferrin, 10-7 mol/L sodium selenite, and 50 mL/L FBS.

Confirmation of PNHH infection with HBV

A test was performed with the isolated DNA to determine whether the HBV- infected PNHHs formed cccDNA. Amplification with primers specific for both outside regions was performed with the isolated DNA because the region was specific for cccDNA rather than partially double-stranded DNA found in viral particles. The primers used are (5′-CTATGCTGGGTCTTCCAAATT-3′) which anneals to near the codon for amino acid 80 in human HBc open reading frame (ORF) and (5′-TTTCTGTGTAAACAATATCTG-3′) which anneals to near the codon for amino acid 680 in HBV Pol ORF. Therefore, if cccDNA was present in the isolated DNA, an amplified 1 kb product could be obtained. In this test, DNA isolated from mock-infected PNHHs was used as the negative control. A PCR test was performed with RNA to confirm whether HBV transcripts were produced. Reverse transcription amplification was performed with primers specific for the epsilon regions: (5′-CAACTTTTTTTCACCTCTGCCTA-3′) which anneals to DR1 and the reverse primer (5′-GATCTCGTACTGAAAGGAAAGA-3′). In addition, to detect HBV genome, real-time PCR was also performed as previously described[12].

cDNA array analysis

RNA was isolated using TRIzol reagent (Life Technologies) according to the manufacturer’s instructions. With the total isolated RNA, reverse transcription was performed with Cy5-labeled dUTP in the experimental sample and Cy3-labeled dUTP in the control. Fifty micrograms of RNA, 1.5 ng oligo dT primer, and 1 ng control RNA containing lambda DNA sequences with a poly A sequence at the 3′ ends for reverse transcription, were mixed and volume of the mixture was adjusted to 20 μL. The mixture was incubated at 70°C for 5 min. After incubation, the mixture was quickly cooled on ice. With this whole reaction mixture, the labeling reaction was performed under the following conditions: 1 × reverse transcription buffer, 0.6 mmol/L Cy3- or Cy5-dUTP, 40 U of RNase inhibitor (Roche), 50 U of AMV-RT (Roche) and a dNTP mix containing 1 mmol/L dATP, 1 mmol/L dGTP, 1 mmol/L dCTP, and 0.4 mmol/L dTTP at 42°C for 1 h. After 1 h, 50 U of AMV-RT was added to the reaction mixture and the mixture was further incubated for 1 h for complete reverse transcription. Reverse transcription was stopped by the addition of 5 μL 0.5 mol/L EDTA. The synthesized cDNA was purified using a chromaspin column (Clonetech) as instructed by the manufacturer and precipitated with ethanol. Both Cy3- and Cy5- labeled cDNAs were resuspended with 100 μL hybridization buffer, containing 6 × standard saline citrate (SSC), 2 g/L sodium dodecyl sulfate (SDS), 5 × Denhardt solution, and 1 mg/mL salmon sperm DNA. The labeled cDNA was used for hybridization to the cDNA microarray chip at 62°C. The chip was arrayed using a GMS417 arrayer (Genetic MicroSystems Inc., Woburn, MA) with 4224 cDNAs and internal standards such as tubulin and actin and external standards such as lambda DNA. After 16-18 h of hybridization, the hybridized array was washed twice at 58°C for 30 min with washing bufferIcontaining 2 × SSC and 2 g/L SDS and washed once with washing buffer II containing 0.05 × SSC at room temperature for 5 min.

Analysis of chips

For quantification of the signals, the chips were scanned using an array scanner generation III (Molecular Dynamics) followed by image analysis using ImaGene ver. 3.0 software (BioDiscovery Ltd., Swansea, UK). The signal intensity of each spot was adjusted to obtain more accurate data by subtracting the background signals from the immediate surroundings. In this analysis, a difference in the ratio of more than two folds was considered significant.

Cells and transfection

HepG2, Huh7, and Chang liver cells were maintained in minimum essential media (Sigma) supplemented with 100 mL/L fetal bovine serum. For reverse transcription-polymerase chain reaction and luciferase reporter assay, cells were seeded in 12- well plates at a density of 0.2 × 106 cells per well and transfected on the following day with the aperopriate DNA and fugene 6 (Roche) as described by the manufacturer. To normalize the total DNA, pUC119 and backbone DNA of pHBV1.2× were used. The transfection efficiency for HepG2 with fugene 6 was usually 10%-20%.

RT-PCR analysis

Cells were transfected with pUC119 and pHBV1.2×. After 48 h of transfection, total RNA was extracted with TRIzol reagent (Life Technologies) as described by the manufacturer. cDNA was produced by reverse transcription using the same procedure as cDNA microarray analysis. Following reverse transcription, the synthesized cDNA was amplified with 2.5 U Hot start Taq polymerase (Takara), GAPDH specific primer set, and appropriate primer set. The sequences of the primer set are as follows: TRAF2 specific forward(5′-AGGGGACCCTGAAAGAATAC-3′), TRAF2 specific reverse(5′-CAGGGCTTCAATCTTGTCTT-3′), NIK specific forward(5′-TACCTCCACTCACGAAGGAT-3′), NIK specific reverse(5′-CAAGGGAGGAGACTTGTTTG-3′), LT-α specific forward(5′-AGCTATCCACCCACACAGAT-3′),

LT-α specific reverse(5′-GTTTATTGGGCTTCATCGAG-3′), GAPDH specific forward(5′-ATCATCCCTGCCTCTACTGG-3′), and GAPDH specific reverse (5′-TGGGTGTCGCTGTTGAAGTC-3′). PCR amplification was performed using Gene mp PCR system 2400 (Perkin-Elmer) with 5 min initial denaturation at 95°C and 35 cycles of 50 s at 95°C, 50 s at 60°C, and 50 s at 72°C, followed by 7 min of extension at 72°C. To separate the PCR fragments, 15% agarose gel was used.

Immunoblot analysis

To confirm NIK and TRAF2 protein expression, we performed immunoblot analysis with anti-NIK rabbit polyclonal antibody (Santa Cruz) and anti-TRAF2 mouse monoclonal antibody (Santa Cruz). HepG2 cells were seeded in 6- well plates at a density of 0.4 × 106 cells per well. Cells were lysed with RIPA buffer containing 25 mmol/L Tris-HCl (pH 7.4), 150 mmol/L KCl, 5 mmol/L EDTA, 10 mL/L Nonidet P-40 (NP-40), 5 g/L sodium deoxycholate, and 1 g/L SDS and centrifuged at 12 000 g for 10 min. The supernatants were separated by 12% SDS-PAGE protein gel for immunoblot analysis.

Luciferase reporter assay

After seeded on 12-well plates, HepG2 cells were co-transfected with appropriate DNA (Figure 5), 0.1 μg pNF-κB-luciferase and 0.1 μg pCMV-β-galactosidase. After 48 h of transfection, cell extracts were prepared and luciferase reporter assay was performed using a luciferase assay system (Promega) as described by the manufacturer. The transfection efficiency was normalized by its galactosidase activity. The assay was triplicated and repeated at least twice.

Figure 5.

Figure 5

Immunoblot assay of TRAF2 and NIK. pUC119 is a backbone DNA about pHBV1.2x. In the HepG2 cells transfected with pHBV1.2x, the protein levels of NIK (A) and TRAF2 (B) were increased. β-actin was used to normalize total protein level.

RESULTS

Confirmation of PNHH infection with HBV

To confirm HBV infection to PNHHs, DNA was isolated during the RNA purification step with TRIzol reagent as instructed by the manufacturer. Infection was confirmed through PCR-based amplification specific only for cccDNA in nuclei of the infected cells. Figure 1 shows that the amplified product appeared in HBV- infected cells, indicating that HBV did infect PNHHs and that the nucleocapsid was transported into nuclei of the infected hepatocytes (Figure 1A). RT-PCR analysis of the HBV transcripts amplified with primers specific for epsilon and polymerase regions as described in Materials and Methods confirmed the presence of HBV RNA transcripts in the infected cells (Figure 1B). Real time PCR showed that HBV was not detected until 6 d after infection (Figure 1C).

Figure 1.

Figure 1

Confirmation of HBV infection for PNHHs using PCR for cccDNA formation and RT-PCR for production of transcripts. From PNHHs infected with HBV, RNA and DNA were extracted using TRIzol reagent as described in Materials and Methods. As a negative control, mock-infected PNHHs were used. A: With the extracted DNA, cccDNA was confirmed by a PCR analysis as described in Materials and Methods; B: With the extracted RNA, a transcript of HBV was confirmed by RT-PCR analysis as described in Materials and Methods; C: With the extracted RNA, a tanscript of HBV was confirmed by real-time PCR as previously described[19].

Raw data analysis

The experiments were carried out in triplicate at the infection step for more certain identification of genes differentially expressed by HBV infection. From each of the HBV infected cells for over 8 d, RNA was isolated and analyzed by microarray. As a result, three sets of cDNA array images were obtained. We analyzed the intensity of the raw image through scatterplot analyses. Figure 2A shows scatterplot analyses of log (Cy3 signal × Cy5 signal) vs log2 (Cy3 signal/Cy5 signal). This showed that each plot tended to divert from the general small curve (Figure 2A). But, each scatterplot analysis of Log (Cy3 signal/Cy5 signal) vs Log (Cy5 signal) showed a curve closer to the exponential decay (Figure 2B). Therefore, the data were fitted to an exponential decay curve for Cy3 per Cy5 channel correction (Figure 2C). Through these steps, we obtained a higher confidence ratio of the Cy3 signal compared to the Cy5 signal for each chip. With the ratios obtained, we analyzed the correlation coefficient between the data of the three chips. The correlation coefficient turned out to be more than 0.7 (Figure 3A), suggesting that the relationship between each chip was significant. The correlation coefficient for genes that were differentially expressed more than two folds was more than 0.95 (Figure 3B). Selected genes that were differentially expressed more than two folds, showed a high reproducibility among the triplicate microarray analyses.

Figure 2.

Figure 2

Scatter plot analysis. For normalization of the Cy3 (3D) and Cy5 channel signal (5D) channels, data obtained from the raw image scanning were plotted in a scatter plot using Excel software (Microsoft). A: The X-axis represents Log2 (3D/5D) and the Y-axis Log2 (3D/5D); B: The X-axis represents Log (5D) and the Y-axis Log (3D/5D); C: The X-axis represents Log (5D) and the Y-axis Log (3D/5D) F, in which “F” is the function for normalization. The bottom panel shows data with signals fitted to an exponential decay curve.

Figure 3.

Figure 3

Correlation between three sets of PNHHs infected for eight days. A: With the reliable signals in obtained signals, the correlation efficient was calculated between each experiment; B: In addition, another correlation efficient was also calculated with only the selected genes, which were differentially expressed more than 2 folds.

Analysis of differentially regulated genes

Through a microarray analysis of PNHHs infected with HBV, we obtained the profile of 45 genes that were down regulated more than two folds compared to the control. The 45 down-regulated genes were analyzed classified by function (Table 1). Table 1 shows that many transcription factors related to RNA polymerase II, were down-regulated by HBV infection. In contrast, transcription factors such as C/EBP, which is used for transcription of HBV genes[19,20], were not differentially expressed. That is, the C/EBP expression level was changed less than two folds.

Table 1.

Forty-five differentially down-regulated genes obtained and categorized by their function

Categoty UniGene Gene nam Symbol Locus Function Control/ HBV infection P-value
Transcription/ RNA Pol II Hs.442675 Thyroid hormone receptor interactor 8 TRIP8 10 Transcription co-activator of Pol II promoter 3.469 0.030
Transcription Hs.57475 Sex comb on midleg homolog 1 SCMH1 1p34 Pol II transcription 3.315 0.019
Transcription Hs.119014 Zinc finger protein 175 ZNF175 19q13.4 C2H2 zinc-finger protein 175 2.942 0.017
Transcription/ RNA Pol II Hs.437905 Spi-B transcription factor (Spi-1/PU.1 related) SPIB 19q13.3-q13.4 RNA polymerase II transcription factor 2.743 0.017
Transcription/ RNA Pol II Hs.148427 LIM homeobox protein 3 LHX3 9q34.3 RNA Pol 2 transcription factor and activate pituitary hormone genes 2.492 0.006
Signal Hs.17154 Dual-specificity tyrosine-(Y)- phosphorylation regulated kinase 4 DYRK4 12p13.32 Dual-specificity protein kinase 4 3.938 0.005
Signal Hs.262886 Inositol polyphosphate-5- phosphatase, 145kD INPP5D 2q36-q37 Modulating cytokine signaling within the hemopoietic system 3.587 0.009
Signal Hs.75249 ADP-ribosylation factor-like 6 interacting protein ARL6IP 16p12-p11.2 Activator of phospholipase D (PLD) 2.801 0.010
Tumor/Suppress Hs.77793 c-src tyrosine kinase CSK 15q23-q25 Downregulate the tyrosine kinase activity of the c-src oncoprotein 3.377 0.021
Tumor/Induce Hs.89839 EphA1 EPHA1 7q34 Overexpression of EPH mRNA was found in a hepatoma 3.039 0.022
Tumor/Induce Hs.79070 V-myc avian myelocytomatosis viral oncogene homolog MYC 8q24.12-q24.13 Promotes cell proliferation and transformation 2.357 0.011
Immune response Hs.118354 Human MHC Class I region proline rich protein mRNA CAT56 6p21.32 Immune response 2.588 0.024
Miscellaneous Hs.180610 Splicing factor proline/ glutamine rich SFPQ 1p34.3 Pre-mRNA splicing factor required for pre-mRNA splicing 10.471 0.006
Miscellaneous/ Cytoskeleton Hs.75064 Tubulin-specific chaperone c TBCC 6pter-p12.1 Cofactor in the folding pathway of beta-tubulin 10.2 0.020
Miscellaneous Hs.438683 BCM-like membrane protein precursor SBB142 1q23.1 BCM-like membrane protein precursor 3.751 0.004
Miscellaneous Hs.8203 Endomembrane protein emp70 precursor isolog LOC56889 10q24.2 Low similarity to human endosomal protein P76 3.502 0.038
Miscellaneous Hs.311609 Nuclear RNA helicase, DECD variant of DEAD box family DDXL 19p13.13 Member of the DEAD/H box ATP- dependent RNA helicase family 2.868 0.026
Miscellaneous/ Energy Hs.150922 BCS1 (yeast homolog)-like BCS1L 2q33 Function in the assembly of complex III of the respiratory chain 2.682 0.007
Miscellaneous Hs.6679 hHDC for homolog of Drosophila headcase LOC51696 6q23-q24 hHDC for homolog of Drosophila headcase 2.611 0.020
Miscellaneous Hs.5300 Bladder cancer associated protein BLCAP 20q11.2-q12 Appears to be down-regulated during bladder cancer progression 2.459 0.028
Miscellaneous Hs.179526 Upregulated by 1, 25-dihydroxyvitamin D-3 VDUP1 1q21.2 Upregulated by 1, 25-dihydroxyvitamin D-3 2.394 0.043
Miscellaneous Hs.440961 Calpastatin CAST 5q15-q21 Inhibitor of the cysteine (thiol) protease calpain 2.276 0.000
Miscellaneous Hs.275775 Selenoprotein P, plasma, 1 SEPP1 5q31 An oxidant defense in the extracellular space 2.186 0.007
EST Hs.371233 ESTs Xp22.3 Moderately similar to T08795 hypothetical protein DKFZp586J1822.1 7.826 0.025
EST Hs.229338 ESTs X 4.687 0.007
EST Hs.212957 ESTs 3q26.1 Moderately similar to ZN91_HUMAN ZINC FINGER PROTEIN 91 4.611 0.019
EST Hs.211823 ESTs 2q37.1 4.519 0.030
EST Hs.57836 ESTs 17 3.323 0.029
EST Hs.87912 ESTs 14q24.1 3.314 0.013
EST Hs.12429 ESTs FLJ22479 4q26-q27 Hypothetical protein FLJ22479 3.217 0.041
EST Hs.213586 ESTs 7 2.759 0.044
EST Hs.2755711 ESTs 22 Weakly similar to T20379 hypothetical protein 2.723 0.019
EST Hs.191435 ESTs 8p23.1-p22 Weakly similar to S65657 alpha-1C- adrenergic receptor splice form 2 2.638 0.023
EST Hs.31293 ESTs 9p13.1 2.286 0.035
Predicted protein Hs.414464 Hypothetical protein HSD3.1 14q31.3 7.314 0.008
Predicted protein Hs.100914 Hypothetical protein FLJ10352 FLJ10352 18p11.21 6.239 0.006
Predicted protein Hs.181112 HSPC126 protein HSPC126 13q14.12 3.322 0.045
Predicted protein Hs.306711 KIAA1081 protein ELKS 12p13.3 3.122 0.036
Predicted protein Hs.101891 KIAA1193 protein KIAA1193 19p13.3 Weakly similar to RPB1_HUMAN DNA-directed RNA Pol II largest subunit 3.029 0.030
Predicted protein Hs.272759 KIAA1457 protein KIAA1457 12q24.31 2.98 0.020
Predicted protein Hs.172089 Homo sapiens mRNA; cDNA DKFZp586I2022 11q22.1 2.784 0.036
Predicted protein Hs.7049 Hypothetical protein FLJ11305 FLJ11305 13q34 2.65 0.028
Predicted protein Hs.445255 KIAA0368 protein KIAA0368 9q32 2.423 0.016
Predicted protein Hs.192190 KIAA0782 protein KIAA0782 11q13.3 2.332 0.009
Predicted protein Hs.169910 KIAA0173 gene product KIAA0173 2p24.3-p24.1 Similar to S72482 hypothetical protein 2.171 0.014

From the analysis by cDNA microarray, 53 up-regulated genes were identified by an increase of more than two folds in their differential expression. Table 2 shows that growth- and tumor-related molecules comprised a proportion of the up-regulated genes. The positive effector genes for tumor and proliferation have found to be GDF11[21] and NOL1[22] and the negative effector genes EXTL3[23] and RAD50. The most interesting genes have found to be the TNF signaling pathway- related genes. LT-α is an inflammatory cytokine and induces the TNF signaling pathway as a ligand for TNF receptor (TNFR). LT-α binds to TNFR and recruits TRAF2. MAP3K14 (NF-κB inducing kinase, NIK) binds to TRAF2 and activates NF-κB[24]. LT-α, TRAF2, and NIK were also up-regulated in the experiment (Table 2). This means that HBV activates NF-κB through up-regulation of LT-α, TRAF2, and NIK.

Table 2.

Fifty-three differentially up-regulated genes obtained and categorized by their function

Categoty UniGene Gene name Symbol Locus Function Control/HBV infection P-value
Signal Hs.82887 Protein phosphatase 1, regulatory (inhibitor) subunit 11 PPP1R11 6p21.3 Soluble protein phosphatase inhibitor(reppresor) 3.623 0.026
Signal Hs.437575 TNF receptor-associated factor 2 TRAF2 9q34 Required for activation of NFkappaB 3.23 0.026
Signal Hs.6527 G protein-coupled receptor 56 GPR56 16q13 Member of the G protein-coupled receptor family 2.817 0.009
Signal Hs.29203 Homo sapiens G protein beta subunit mRNA, partial cds GBL 16p13.3 G protein-linked receptor protein for signalling pathway 2.76 0.009
Signal/ Cytoskeleton Hs.2157 Wiskott-Aldrich syndrome WAS Xp11.4-p11.21 Involved in transduction of signals from receptors on the cell surface to the actin cytoskeleton 2.446 0.018
Signal Hs.440315 Mitogen-activated protein kinase kinase kinase 14 MAP3K14 17q21 Binds to TRAF2 and stimulates NF-kappaB activity 2.185 0.043
Tumor/ Induce Hs.15243 Nucleolar protein 1 (120kD) NOL1 12p13.3 Transforms NIH3T3 cells when overexpressed 5.273 0.004
Tumor/ Supress Hs.9018 Exostoses (multiple)-like 3 EXTL3 8p21 Tumor suppressor, glycosyltransferase activity 5.07 0.093
Tumor/ Supress Hs.41587 RAD50 (S. cerevisiae) homolog RAD50 5q31 Associates with MRE11, nibrin (NBS1) and the tumor suppressor BRAC1 2.443 0.013
Growth/ Positive Hs.511740 Growth differentiation factor 11 GDF11 12q13.13 Regulators of cell growth and differentiation in both embryonic and adult tissues 2.969 0.023
Cell cycle/ Negative Hs.76364 Allograft inflammatory factor 1 AIF1 6p21.3 Involved in negative regulation of growth of vascular smooth muscle cells 3.573 0.031
Cell cycle/ Positive Hs.25313 Microspherule protein 1 MCRS1 12q13.12 Involved in cell-cycle-dependent stabilization of ICP22 in HSV1- infected cells 3.273 0.044
Cell cycle/ Positive Hs.371833 Nuclear receptor binding factor-2 NRBF-2 10 A possible gene activator protein interacting with nuclear hormone receptors 2.568 0.018
Cell cycle/ Positive Hs.440606 Centrosomal protein 2 CEP2 20q11.22-q12 Regulate centriole-centriole cohesion during the cell cycle 2.422 0.022
Enzyme/ Glycosylation Hs.4814 Mannosidase, alpha, class 1B, member 1 MAN1B1 9q34 N-linked glycosylation 3.097 0.008
Enzyme/ lysophospholipase Hs.889 Charot-Leyden crystal protein CLC 19q13.1 Phospholipid metabolism and anti-pathogen 3.065 0.035
Enzyme/Protease Hs.75890 Site-1 protease MBTPS1 16q24 A sterol-regulated subtilisin-like serine protease 2.873 0.023
Immune response Hs.2014 T cell receptor delta locus TRD@ 14q11.2 T-cell antigen receptor, delta polypeptide 3.69 0.023
Immune response Hs.465511 Granzyme M GZMM 19p13.3 Serine protease for anti-pathogen response 3.201 0.023
Transcription Hs.436871 Zinc finger protein 173 ZNF173 6p21.3 DNA/protein binding, transcriptional protein 3.411 0.002
Transcription Hs.108139 Zinc finger protein 212 ZNF212 7q36.1 DNA/protein binding, transcriptional protein 2.341 0.045
Apoptosis Hs.36 Lymphotoxin alpha LTA 6p21.3 A member of the tumor necrosis factor family 14.912 0.019
Miscellaneous Hs.434384 Titin TTN 2q31 Large myofilament protein 4.087 0.012
Miscellaneous Hs.58927 Nuclear VCP-like NVL 1q41-q42.2 Member of the AAA family of ATPases 4.005 0.035
Miscellaneous Hs.122552 G-2 and S-phase expressed 1 GTSE1 22q13.2-q13.3 Accumulates in late S/G2 phase, is phosphorylated in mitosis, and disappears in G1 phase 3.491 0.007
Miscellaneous/Glycosylation Hs.82921 Solute carrier family 35 (CMP- sialic acid transporter), member 1 SLC35A1 6q15 Important for normal sialylation of glycoproteins and glycolipids 3.352 0.013
Miscellaneous Hs.410455 Unc119 (C.elegans) homolog UNC119 17q11.2 May function in photoreceptor neurotransmission 3.328 0.030
Miscellaneous Hs.55041 CGI-22 protein MRPL2 6p21.3 Unknown 3.052 0.01
Miscellaneous/Cytoskeleton Hs.74088 Bridging integrator-3 BIN3 8q21.2 Related to actin assembly- competent state 2.677 0.018
Miscellaneous Hs.25237 Mesenchymal stem cell protein DSCD75 LOC51337 8q24.3 Moderately similar to uncharacterized Drosophila CG4666 2.615 0.042
EST Hs.95867 Homo sapiens EST00098 gene, last exon EST00098 9q34.1 8.781 0.027
EST Hs.98785 ESTs KSP37 4p16 3.749 0.011
EST Hs.136912 ESTs MGC10796 3q13.13 3.435 0.003
EST Hs.101774 ESTs FLJ23045 20p11.23 3.387 0.032
EST Hs.420262 ESTs 13 3.355 0.022
EST Hs.124840 ESTs 11q13.1 3.114 0.021
EST Hs.272299 ESTs RP4-622L5 1p36.11-p34.2 3.008 0.034
EST Hs.415048 ESTs 5 2.891 0.025
EST Hs.531268 ESTs 16 2.889 0.013
EST Hs.273830 ESTs FLJ12742 1 2.739 0.020
EST Hs.190162 ESTs 1p32.3 2.708 0.021
EST Hs.303172 ESTs 18 2.578 0.04
EST Hs.59203 ESTs 7 2.437 0.022
EST Hs.231444 ESTs 1 2.343 0.005
Unknown sequence Hs.284265 Homo sapiens pRGR1 mRNA, partial cds 6q27 2.966 0.043
Unknown sequence Hs.291385 Homo sapiens clone 23664 and 23905 mRNA sequence 4p14-p12 2.439 0.041
Predicted protein Hs.31718 Homo sapiens cDNA FLJ11034 fis, clone PLACE1004258 VRL 17.359 0.000
Predicted protein Hs.61960 Hypothetical protein FLJ20040 16p13.3 9.166 0.002
Predicted protein Hs.274552 Homo sapiens cDNA FLJ10720 fis, clone NT2RP3001116 FLJ10720 5 4.751 0.015
Predicted protein Hs.279761 HSPC134 protein HSPC134 14q11.2 3.501 0.038
Predicted protein Hs.283716 Hypothetical protein PRO1584 PRO1584 8p21.2 3.493 0.033
Predicted protein Hs.464526 Homo sapiens clone 23649 and 23755 unknown mRNA, partial cds 18q11.2 3.198 0.032
Predicted protein Hs.274412 Homo sapiens cDNA FLJ10207 fis, clone HEMBA1005475 UPF3A 17p11.2 3.076 0.012

RT-PCR analysis and immunoblot assay of selected genes

According to the cDNA microarray data, three genes related to the TNF signaling pathway, LT-α, TRAF2, and NIK, were up-regulated. Upregulation of these genes was confirmed by RT-PCR. For RT-PCR analysis, primer sets specific to LT-α, TRAF2, and NIK, were used and experiments were performed in hepatoma-derived cell lines, including HepG2, Huh7, and Chang liver cells. As a result, the mRNA levels of these three genes in each cell line were increased by pHBV1.2× transfection (Figure 4). In addition to RT-PCR, the expression of NIK and TRAF2 was confirmed at the protein level (Figure 5). The expression of LT-α, was confirmed by immunofluorescence staining analysis (data not shown).

Figure 4.

Figure 4

RT-PCR analysis of selected genes. Mock means untransfected cells. pUC119 is backbone of pHBV1.2x, so pUC119 transfected cells are the negative control for pHBV1.2x transfected cell. In the hepatoma-derived cell lines, HepG2, Huh7, and Chang liver cells, TRAF2, NIK, and LT-α mRNA level in pHBV1.2x transfected cells were up-regulated rather than mock and pUC119 transfected cells.

NF-κB activation through TRAF2, NIK mRNA up regulation

According to cDNA microarray and RT-PCR analysis, mRNA expression of LT-α, TRAF2, and NIK was up-regulated by HBV. Since their expression was related to NF-κB activation. HBV-mediated NF-κB activation might be involved in the up regulation of these genes. To determine whether these genes actually are involved in HBV-mediated NF-κB activation, we performed a luciferase assay with a pNF-κB-luciferase vector as a reporter plasmid. To elucidate whether HBV-mediated NF-κB activation is dependent on TRAF2 and NIK of three genes, we cotransfected pTRAF2 DN or pNIK DN, the dominant negative form of pTRAF2 or pNIK, with pNF-κB-luciferase, pCMV β-galactosidase, and pHBV1.2× (Figure 6). The experiment for LT-α was performed with anti- LT-α, to neutralize LT-α. The pHBV1.2× produced about a 4.2 folds greater increase in NF-κB luciferase activity than pUC119. However, pHBV1.2× cotransfection with TRAF2 DN or NIK DN produced about a 3.5 or 1.2 fold relative increase (Figure 6) and treatment with anti- LT-α decreased the ratio to less than 4.2 folds (data not shown). These findings led us to think that HBV could activate NF-κB and that this HBV-mediated NF-κB activation might require LT-α, TRAF2, and NIK. DC.

Figure 6.

Figure 6

HBV-mediated NF-κB activation through TRAF2 and NIK. In pHBV1.2x transfected HepG2 cells, NF-κB activity was increased more than pUC119 transfected cells. But in cotransfected cells with pHBV1.2x and TRAF2 DN or NIK DN, NF-κB activity was decreased less than pHBV1.2x transfected cells.

DISCUSSION

In this report, we focused on the interaction between HBV and hepatocytes during the initial stage of infection. To mimic hepatocyte infection with HBV under in vivo conditions, we isolated PNHHs and infected them with HBV. We chose this method because cultured cell lines such as HepG2 are seldom infected with HBV[25,26], and transformed cultured cells have many physiological properties that are altered in the original state of hepatocytes[27,28]. In this experiment, the same hepatocytes were used as a control. Since they are produced under identical conditions, a pair of samples of the same genetic background could be obtained. With these samples, we were able to analyze differentially expressed genes. As a result, we obtained gene expression profiles and 98 consistently differentially expressed genes were identified by gene expression profiles. Of these genes, 53 were up-regulated and 45 down-regulated. It was reported that there are no genes uniformly correlated with HBV DNA profile during the initial host response to HBV infection[29]. However, because this study was performed on chimpanzees, there are some considerations in making a comparision between this study with our report. Our report analyzed the effect of HBV on PNHHs at cellular level without any other cell types, including immunocytes. So the influence of immunocytes was not included in this analysis. In addition, the difference in human beings and chimpanzees needs to be taken into consideration.

The results of our study showed that a proportion of the down-regulated genes was transcription factor-related genes and a proportion of the up-regulated genes was TNF signaling pathway-related genes. Down regulation of transcription factors may be helpful for the transcription of the HBV gene because the transcripts of the host cell can be repressed and the transcriptional machinery can be efficiently used for viral transcription. C/EBP, which is involved in viral genome transcription[19,20], had no substantial differential expression in this experiment. In addition to down regulation of transcription factor for virus transcription, up regulation of cell proliferation-related genes may help viral replication. Of the up-regulated genes, LT-α, TRAF2, and NIK may induce cell proliferation via NF-κB activation.

In fact, LT-α is mainly related to the signal cascade for apoptosis and generally involves the host defense system[30]. However LT-α is also related to cell proliferation. Usually, TNF signaling including LT-α, can induce apoptosis and proliferation[31]. TNF signaling by LT-α has a signal cascade from TNFR to TRADD. In the case of apoptosis, TRADD-FADD interaction is needed to activate caspase 8[31]. In the case of proliferation, TRADD-TRAF2 interaction induces activation of NF-κB, a proliferation-inducing transcription factor[31]. After TRAF2 binds to TRADD, NIK binds to TRAF2 and activates NF-κB through IKK activation and IκB-α degradation[24,32-34]. In cDNA microarray data, among genes related to the two opposite effects initiated by LT-α, proliferation-related genes are up-regulated. FADD is not differentially altered by more than two folds. Therefore, HBV infection may strengthen the TNF signaling pathway to cell proliferation through the induction of gene expression.

In conclusion, HBV induces NF-κB activation by upregulating LT-α, TRAF2, and NIK, and cell proliferation by activating NF-κB.

ACKNOWLEDGMENTS

The authors thank Dr. SY Lee for providing pTRAF2 and pTRAF2 DN vector.

Footnotes

Supported by a grant of the Korea Health 21 R&D Project, Ministry of Health and Welfare, Republic of Korea, No. A050145

S- Editor Wang J L- Editor Wang XL E- Editor Ma WH

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