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1 Department of Virology, Bernhard Nocht Institute for Tropical Medicine, 20359 Hamburg, Germany
2 Mucosal Immunity Group, German Research Centre for Biotechnology, 38124 Braunschweig, Germany
Correspondence
Stephan Günther
guenther{at}bni.uni-hamburg.de
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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) gene expression was studied longitudinally in Lassa virus-infected HuH-7 and FRhK-4 cells by using real-time RT-PCR. IFN- mRNA levels increased only twofold upon Lassa virus infection, although there was no evidence that the virus inhibited poly(I : C)-induced IFN- gene expression. In conclusion, Lassa virus interferes only minimally with gene expression in HuH-7 cells and poorly induces IFN- gene transcription. Supplementary material is available in JGV Online.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). In view of the paucity of histopathological changes, it has often been speculated that Lassa virus induces pathological changes at the subcellular level.
A common technology for studying virus–host-cell interaction at the molecular level is transcriptional profiling by using micro- or macroarrays. Arrays facilitate simultaneous quantification of mRNA steady-state levels for thousands of cellular genes. This recent technology has been useful in identifying changes in gene expression both in cultured cells and in whole organisms infected with pathogens. Transcriptional changes were described in cells infected with various RNA viruses, including measles virus (Bolt et al., 2002), reovirus (DeBiasi et al., 2003; O'Donnell et al., 2006), hantavirus (Geimonen et al., 2002; Prescott et al., 2005), pneumovirus (Munir & Kapur, 2003), respiratory syncytial virus (Zhang et al., 2001), influenza A virus (Geiss et al., 2001), dengue virus (Warke et al., 2003), coronaviruses (Tang et al., 2005) and filoviruses (Kash et al., 2006). Cells infected with Lassa virus or LCMV have not yet been investigated by using transcriptional arrays. As the liver is a major target organ of Lassa virus (McCormick et al., 1986), we studied gene expression in Lassa virus- or LCMV-infected HuH-7 cells, a differentiated human hepatoma cell line (Nakabayashi et al., 1982). Two different types of array were used: cDNA-based macroarrays with a representative set of 3500 genes (Atlas Human 1.2 arrays; Clontech) and oligonucleotide-based microarrays covering 18 400 transcripts and variants, including 14 500 well-characterized human genes (Human Genome U133A array; Affymetrix). Additional experiments were performed to characterize beta interferon (IFN-) gene expression in Lassa virus-infected cells.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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; Schmitz et al., 2002). LCMV strains WE and Armstrong (ARM) (kindly provided by Michael Bruns, Heinrich-Pette-Institute, Hamburg, Germany) underwent an unknown number of passages. Hepatitis A virus (HAV) was kindly provided by Andreas Dotzauer (Institute of Virology, University of Bremen, Germany).
Virus infection.
Infection with Lassa virus and LCMV was carried out under biosafety level (BSL)-4 and BSL-3 conditions, respectively. For transcription arrays, HuH-7 cells were seeded at a density of 1x106 cells per 120 mm diameter culture dish 24 h before infection. Cells were infected at an m.o.i. of 0.01. After 1 h, cells were washed with PBS and 10 ml medium was added. Cells and supernatant were harvested 3 days post-infection and RNA was prepared. Control cells were treated like infected cells, except that the inoculum did not contain virus.
For measurement of IFN- mRNA levels, HuH-7 and FRhK-4 cells were seeded at a density of 6x104 cells per well of a 24-well plate 24 h prior to infection. Cells were infected with Lassa virus AV and HAV at an m.o.i. of 0.01 and 1, respectively, or were left uninfected. After 1 h, cells were washed with PBS and 500 µl medium was added. Three and four days after infection with Lassa virus and HAV, respectively, cells were transfected with 50 µl transfection mix per well, containing 4.2 µg poly(I : C) (Sigma) and 12.6 µl Transfectin (Bio-Rad), or were left untreated. Medium was replaced after 4 h. Cells were harvested 16 h after transfection and RNA was prepared. For longitudinal measurement of IFN- mRNA levels, cells were infected with Lassa virus AV at an m.o.i. of 1 and RNA was prepared 16, 24 and 48 h after infection.
Immunofluorescence.
Lassa virus- and LCMV-infected cells were spotted onto glass slides, air-dried and fixed in acetone. Cells were incubated with LCMV nucleoprotein (NP)-specific monoclonal antibody 53 (kindly provided by Michael Bruns, Heinrich-Pette-Institute, Hamburg, Germany) or Lassa virus NP-specific antibody L2F1 (Hufert et al., 1989) for 1 h at 37 °C. After washing three times in PBS, rhodamine-labelled anti-mouse IgG antibody was added for 1 h. Slides were washed and analysed by fluorescence microscopy.
RNA preparation.
Total RNA was prepared with an RNeasy kit (Qiagen) according to the manufacturer’s protocol. Infected cells were lysed in 1 ml buffer RLT (Qiagen) per 100 mm diameter culture dish or 300 µl per well of a 24-well plate, and homogenized with a QIAshredder (Qiagen). RNA was quantified spectrophotometrically and its integrity was checked by agarose-gel electrophoresis. Quality of RNA preparations for Affymetrix microarray analysis was additionally checked with an Agilent Technologies 2100 Bioanalyzer (see Supplementary Fig. S1, available in JGV Online).
Atlas cDNA array hybridization and data collection.
RNA was labelled radioactively by using a RevertAid First Strand cDNA synthesis kit (MBI Fermentas) and hybridized to Atlas Human 1.2 arrays I, II and III (Clontech) with minor modification to the manufacturer’s protocol. In total, 18 labelling reactions and array hybridizations were performed, as each RNA sample (n=6) had to be processed separately with arrays I, II and III. In brief, 1 µl array-specific CDS primer mix (Clontech) was hybridized to 3 µg RNA in a total volume of 5 µl. The mix was incubated at 70 °C for 2 min and then at 50 °C for 2 min. Reverse transcription was performed at 50 °C for 25 min in a 20 µl assay containing 5 µl RNA–primer mix, 1x RevertAid buffer, 0.5 mM dNTP mix for dATP label, 50 µCi (1.85 MBq) [
-32P]dATP (3000 Ci mmol–1) (Hartmann Analytic), 20 U RNasin (Promega) and 200 U RevertAid reverse transcriptase. The reaction was stopped by addition of 2 µl termination mix (Clontech). Labelled cDNA was purified with NucleoSpin columns (Clontech). The cDNA was denatured under alkaline conditions and added to prehybridized Human 1.2 array I, II or III nylon membranes (depending on the CDS primer mix used). Hybridization was carried out in 5 ml ExpressHyb solution (Clontech) containing 0.5 mg sheared salmon testis DNA at 68 °C overnight. After washing, the membrane was exposed to imaging plates for 3–10 days. Autoradiography signals were scanned with a Typhoon phosphorimager and image data were processed with ImageQuant software (both from Amersham Biosciences).
Raw data were extracted from array images (1176 genes per array) by using AtlasImage 2.01 software (Clontech). Analysis was performed with local background correction, which results in a positive signal value. A gene was defined as present if the value was greater than mean+3SD of background intensity (cut-off value). To calculate the cut-off value, 196 fields of the analysis grid were placed into empty, i.e. background, areas of each array image and mean and SD of the background intensity were calculated. Background intensity values followed a normal distribution. According to the cut-off definition, the following percentages of genes were called present on arrays I, II and III (altogether, 3528 genes): control-1, 47 %; control-2, 42 %; Lassa virus AV-1, 44 %; Lassa virus NL, 39 %; LCMV ARM, 51 %; LCMV WE, 46 %. Expression values of genes called present were global mean-normalized, log2-transformed and local mean-normalized (Loess fit) against the consensus dataset of the respective array (I, II or III) by using the SNOMAD server at http://pevsnerlab.kennedykrieger.org/snomadinput.html (Colantuoni et al., 2002). After normalization, data of arrays I, II and III were pooled, resulting in six datasets: control-1, control-2, Lassa virus AV-1, Lassa virus NL, LCMV ARM and LCMV WE. The final Atlas dataset was compiled from these six datasets and contained 1206 genes. A gene was included if it was present in at least five of the six individual datasets.
Affymetrix microarray hybridization and data collection.
Biotin-labelled target synthesis was performed by using standard protocols supplied by the manufacturer (Affymetrix). Briefly, 5 µg total RNA (n=4 samples) was converted to double-stranded cDNA by using 100 pmol T7T23V primer (Eurogentec) that contains a T7 promoter. The cDNA was then subjected to in vitro transcription in the presence of biotinylated nucleotides to generate biotin-labelled cRNA. The concentration of biotin-labelled cRNA was determined by UV absorbance (A260). About 12.5 µg of each biotinylated cRNA preparation was fragmented and placed in a hybridization cocktail that contained four biotinylated hybridization controls (BioB, BioC, BioD and Cre) as recommended by the manufacturer. All samples were hybridized to the same lot (no. 4001041) of Affymetrix HG-U133A GeneChip (22 000 probe sets) for 16 h. After hybridization, the GeneChips were washed, stained with streptavidin–phycoerythrin and read by using an Affymetrix GeneChip fluidic station and scanner. Microarray data were analysed by using the Affymetrix Microarray Suite (MAS) 5.0, Affymetrix MicroDB 3.0 and Affymetrix Data Mining Tool 3.0. Based on the statistical MAS 5.0 algorithm, the following percentages of genes were called present on the arrays: control-2, 40 %; control-3, 48 %; Lassa virus AV-1, 42 %; Lassa virus AV-2, 49 %. Additional quality-control parameters are provided in Supplementary Table S1, available in JGV Online. Expression data of genes called present were global mean-normalized, log2-transformed and local mean-normalized (Loess fit) against the consensus dataset by using the SNOMAD server. The final Affymetrix dataset was compiled from the four datasets and contained 7677 genes. A gene was included if it was present in all four individual datasets.
Statistical analysis of expression data.
The Atlas dataset (Lassa virus or LCMV versus controls) and the Affymetrix dataset (Lassa virus versus controls) were analysed for statistically significant gene-expression differences by using Cyber-T statistics for control and experimental data (http://visitor.ics.uci.edu/genex/cybert/) (Baldi & Long, 2001). Posterior probability of differential expression (PPDE) analysis was done on P values of log-transformed data (Bayes ln P). Bayesian standard deviation was estimated by using a sliding-window size of 101 and a confidence value of 6.
The Atlas dataset was analysed further by using the multivariate permutation test of ‘Class Comparison between Groups of Arrays’ tool and the ‘Significance Analysis of Microarrays’ (SAM) algorithm of the BRB-ArrayTools 3.3 program package (available from http://linus.nci.nih.gov/BRB-ArrayTools.html). Class comparison (Lassa virus versus LCMV versus control) was performed with 1000 random permutations, a confidence level of false-discovery rate assessment of 90 % and a maximum allowed proportion of false-positive genes of 0.1.
Quantitative real-time RT-PCR.
Virus RNA was isolated from 140 µl cell-culture supernatant of Lassa virus- and LCMV-infected cells by using a QIAamp Viral RNA kit (Qiagen) according to the manufacturer’s instructions. Real-time RT-PCR for Lassa virus and LCMV was performed with a Brilliant Single-Step Quantitative RT-PCR Core Reagent kit (Stratagene), SYBR green as reporter dye and in vitro-transcribed virus RNA as a quantification standard, as described previously (Asper et al., 2004). HAV RNA was quantified with an HAV RT-PCR kit (artus).
Cellular mRNA level was measured by using TaqMan Gene Expression assays (Applied Biosystems) consisting of preformulated PCR primers and a FAM dye-labelled TaqMan probe [assay ID: laminin-alpha 2, Hs00166308_m1; ribosomal protein L28, Hs00760889_s1; interferon-beta 1 (IFN-), Hs00277188_s1]. The 20 µl PCR was based on the Brilliant Single-Step Quantitative RT-PCR Core Reagent kit (Stratagene) and contained 1x buffer, 2 mM MgCl2 (2.5 mM for IFN-), 1.25 U StrataScript reverse transcriptase, 1 U SureStart Taq DNA polymerase, 0.5x TaqMan Gene Expression mix and 1 µg total cellular RNA (200 ng for IFN-). PCR was run on an ABI Prism TaqMan 7000 at 45 °C for 30 min and 94 °C for 10 min, followed by 45 cycles of 95 °C for 15 s and 60 °C for 1 min. The PCR target region of IFN- mRNA was cloned into pT-Adv (AdvanTAge PCR cloning kit; Clontech) and transcribed in vitro by using a MEGAscript kit (Ambion). The in vitro transcripts were used in the PCR to generate standard curves to quantify IFN- mRNA levels.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). Virtually all cells were infected (Fig. 1a) and virus concentration ranged from 108 to 109 copies (ml supernatant)–1 (Fig. 1b). Total RNA was isolated and cellular mRNA levels were quantified by two types of expression array. One set of experiments was performed with Atlas Human 1.2 arrays I, II and III. Between 39 and 51 % of the genes were called present on the filters. The six datasets were divided into three classes: Lassa virus-infected cells (Lassa AV-1 and NL), LCMV-infected cells (LCMV WE and ARM) and control cells (control-1 and -2). To extend and substantiate the data obtained with the cDNA-based Atlas array, expression levels were also measured with the oligonucleotide-based Affymetrix U133A array, covering a larger number of transcripts. Arrays were hybridized with mRNA of two separate infection experiments performed with Lassa virus AV (Lassa virus AV-1 and AV-2) and two controls (control-2 and -3). Between 40 and 49 % of the genes were called present on the filters.
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, respectively. The three scatterplots show no major changes in gene expression due to infection with Lassa virus or LCMV, although the global variability of the Atlas array data was higher than that of the Affymetrix array data. Statistical analysis of the datasets shown in the scatterplots was performed with Cyber-T software. This program uses a Bayesian approach and is particularly suited to the analysis of datasets with a low number of replicates. Furthermore, the program calculates a PPDE, i.e. it estimates the rate of false positives. Analysis of Lassa virus (AV-1 and NL) versus control (1 and 2) data of the Atlas array revealed only four genes with a fold change between 4.2 and 10.4 (i.e. higher expression value in the infected cells) and three genes with a fold change between –3.4 and –5.7 (i.e. higher expression value in the controls) that had a PPDE of >90 % (see Supplementary Table S2, available in JGV Online, for a list of genes with the highest PPDE values). Analysis of LCMV (WE and ARM) versus control (1 and 2) data from the Atlas array did not reveal any gene with a PPDE of >90 % (see Supplementary Table S3 for a list of genes with the highest PPDE values). The same result was found when Lassa virus versus LCMV data were analysed (data not shown). To substantiate the Cyber-T analysis, the Atlas array datasets (Lassa virus, LCMV and control) were analysed by two additional tests that control number and proportion of false discoveries. When the comparison was performed with a multivariate permutation test (BRB-ArrayTools) at 90 % confidence that the gene-discovery list contains no more than 10 % false discoveries, only ribosomal protein L28 was identified as being statistically significant. The SAM algorithm did not disclose a significant gene at all. In conclusion, the statistical tests suggest that most, if not all, of the expression differences detected by the Atlas array (Supplementary Tables S2 and S3, available in JGV Online) do not represent ‘true’ positives.
To verify this, two additional analyses were performed. First, the expression levels of the two genes showing the largest signal differences in both Lassa virus- and LCMV-infected cells, namely laminin-alpha 2 and ribosomal protein L28 (encircled in Fig. 1c, d; Supplementary Tables S2 and S3), were tested by real-time RT-PCR. The laminin-alpha 2 mRNA level was at the detection limit of the PCR in all samples, suggesting a generally low expression level. Real-time RT-PCR also did not detect an elevated level of ribosomal protein L28 mRNA in virus-infected cells. Second, the Atlas array data for Lassa virus were compared with the Affymetrix array data. None of the 20 genes with the largest signal differences in the Atlas array showed a corresponding signal difference in the Affymetrix array (Supplementary Table S2, available in JGV Online).
The Affymetrix array data (Lassa virus AV-1 and AV-2 versus control-2 and -3; Fig. 1e) were also analysed by Cyber-T. The program was not able to calculate PPDE values, indicating the lack of ‘true’ differential expression. Even the genes with the lowest ‘Bayes ln P’ values showed only minimal expression differences (ranging from –2.1 to 2.1), and these differences were often not supported by additional probe sets targeting the same gene (Supplementary Table S4, available in JGV Online). In conclusion, analysis of mRNA levels in HuH-7 cells using two array technologies did not provide evidence for significant gene-expression changes during productive Lassa virus infection.
As the array analysis was performed at the late phase of infection, an early upregulation of IFN- gene transcription might have escaped detection. Therefore, further experiments were performed to: (i) confirm the lack of IFN- gene activation with a different experimental setup; (ii) verify that the HuH-7 cells used in our study are competent for IFN- induction; and (iii) test whether Lassa virus counteracts IFN- gene induction. HAV was included in the experiments as a control because it is known to interfere with IFN- gene induction (Brack et al., 2002). Two cell lines, human HuH-7 cells and FRhK-4 cells from rhesus monkeys, were transfected with the IFN-inducing double-stranded RNA analogue poly(I : C). IFN- gene expression was measured 16 h after transfection by real-time RT-PCR. Poly(I : C) stimulated the expression of the IFN- gene in both cell lines, although the level of activation was considerably higher in FRhK-4 cells. In contrast to poly(I : C), infection with Lassa virus at an m.o.i. of 1 increased IFN- mRNA levels only marginally between 16 and 48 h post-infection (Fig. 2a, c, right). In order to study whether Lassa virus, like HAV, antagonizes double-stranded RNA-induced IFN- gene expression, cells were first infected with virus and then transfected with poly(I : C). Poly(I : C) transfection was performed at a time when virtually all cells were infected, as tested by immunofluorescence (data not shown). Lassa virus and HAV replication in the poly(I : C)-transfected cells was also verified by real-time RT-PCR (Fig. 2e). HAV blocked poly(I : C)-stimulated IFN- gene expression nearly completely, whereas Lassa virus had no suppressive effect at all (Fig. 2). These data indicate that Lassa virus stimulates IFN- gene expression only marginally in HuH-7 and FRhK-4 cells. However, it does not seem to antagonize double-stranded RNA-induced IFN- gene expression.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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mRNA levels by real-time RT-PCR indicated that Lassa virus stimulates IFN- gene expression poorly in both HuH-7 and FRhK-4 cells. On the other hand, the virus does not seem to antagonize the induction of IFN-. These data suggest minimal interaction between Lassa virus and the host-cell transcriptional machinery, as well as the IFN- induction pathway.
The lack of significant changes in gene expression is somewhat surprising in view of various reports on the influence of other RNA viruses on host-cell transcription in cell culture (DeBiasi et al., 2003; Geimonen et al., 2002; Geiss et al., 2001; Kash et al., 2006; Munir & Kapur, 2003; O'Donnell et al., 2006; Prescott et al., 2005; Tang et al., 2005; Warke et al., 2003; Zhang et al., 2001). There could be methodological as well as biological reasons for these differences. First, one might speculate that our experimental system is not suitable for measuring gene-expression changes. However, HuH-7 is a widely used cell line for microarray experiments. These cells have been used to study the cellular response to individual proteins of hepatitis C virus (HCV) (Dou et al., 2005; Fukutomi et al., 2005; Girard et al., 2002, 2004; Li et al., 2002) and hepatitis B virus (Locarnini et al., 2005), to HCV replicon (Geiss et al., 2003; Hayashi et al., 2005; Scholle et al., 2004) and to infections with Ebola and Marburg virus (Kash et al., 2006) or with severe acute respiratory coronavirus and human coronavirus 229E (Tang et al., 2005). In the present study, HuH-7 cells were infected at low m.o.i. to facilitate productive infection and to prevent accumulation of defective interfering particles (Bruns et al., 1988). The array analysis was done after 3 days when virtually all cells expressed high levels of NP. We assumed that this experimental design most closely resembles an acute infection in vivo and that, in particular, the accumulation of virus proteins during the late phase might induce a cellular response relevant to molecular pathogenesis. The observed minimal changes in host-cell transcription during this phase would be consistent with the fact that arenaviruses are non-cytolytic viruses that, at least in their natural hosts, can replicate to high titres without causing overt cell pathology. On the other hand, as the cells were not synchronized with respect to the initiation of infection, early transcriptional changes may not be detected in our analysis. Such changes were at least excluded for the IFN- gene by infection experiments at high m.o.i. (see below).
The main reason that we accepted the hypothesis that there is no differential gene expression (statistically speaking, the null hypothesis) was the stringent statistical analysis. In contrast to many previous publications, the analysis was based on statistical frameworks that control the false-discovery rate, and we performed a comparative analysis with two types of array. However, the data do not necessarily mean that there is no differential gene expression due to Lassa virus infection. The changes may be too small to be detected with statistical significance in consideration of the precision of the arrays and the number of replicates tested (Wei et al., 2004). The scatterplots (Fig. 1) and the fold change values in Supplementary Tables S2–S4 (available in JGV Online), which have been classified by the statistical programs as probable false discoveries, suggest that a ‘true’ expression difference should be greater than two- and fourfold to be identifiable in the Affymetrix and Atlas array, respectively, using our experimental design. In other words, potential expression changes due to Lassa virus infection are likely to be smaller than twofold. Model calculations indicate that the number of necessary replicates increases considerably if 1.5-fold changes are detected at a reasonably low false-discovery rate (Wei et al., 2004).
To our knowledge, this is the first study to apply both Atlas and Affymetrix arrays, facilitating a direct comparison of both technologies. In our hands, the Affymetrix technology was superior in terms of workload, data collection, precision and final volume of data. For two genes, statistically ‘true’ signal differences were found in the Atlas array, which could not be verified by real-time RT-PCR or Affymetrix array. The reason for this discrepancy is not clear, although cross-hybridization of Lassa virus and LCMV sequences with the cDNA on the filter might have contributed. Careful verification of signal differences on Atlas array filters is recommended.
Whilst HuH-7 cells have the advantage of showing differentiated liver-cell functions (Nakabayashi et al., 1982), they are probably not the cell line of choice for studying IFN induction. HuH-7 cells are less responsive than other hepatoma cells to Sendai virus infection or poly(I : C) transfection (Li et al., 2005; McCormick et al., 2004). Therefore, the array data for IFN- were validated not only with HuH-7 cells, but also with FRhK-4 cells, by using real-time RT-PCR. Although we were able to stimulate IFN- gene expression to some extent in our HuH-7 cells, indicating that this pathway is not defective, FRhK-4 cells responded considerably better to poly(I : C). The latter cells are also responsive to Newcastle disease virus (Fensterl et al., 2005) and Sendai virus (S. Müller & S. Günther, unpublished data) infection. In contrast to these viruses, Lassa virus, even after high-dose inoculation, increased the IFN- mRNA level only marginally. This is consistent with previous data showing that dendritic cells and macrophages are not activated by infection with Lassa virus (Baize et al., 2004; Mahanty et al., 2003). They fail to secrete proinflammatory cytokines, do not upregulate costimulatory molecules and stimulate proliferation of T cells poorly. These and our results are in line with the hypothesis that Lassa virus is a poor inducer of the innate immune response. On the other hand, we have tested gene expression in an isolated hepatocyte culture, whereas the liver contains other cell types that may express cytokines in response to infection that could account for the liver pathology seen in humans and non-human primates (McCormick et al., 1986).
The molecular basis by which Lassa virus prevents induction of IFN- remains unclear. Several viruses, such as HAV, Ebola virus and influenza A virus, express interferon antagonists that inhibit IFN- gene expression (Basler et al., 2000; Brack et al., 2002; Talon et al., 2000). Very recently, it has been shown that NP of LCMV inhibits Sendai virus-induced IFN expression by preventing nuclear translocation of IFN-regulatory factor 3 (Martinez-Sobrido et al., 2006). We could not provide experimental evidence for inhibition of poly(I : C)-induced IFN- gene expression in Lassa virus-infected cells, although the control experiments with HAV confirm the validity of the experimental system. It seems that the virus escapes the pathogen-recognition pathways without inhibiting them, a hypothesis that has also been put forward for mouse hepatitis virus (Zhou & Perlman, 2007). Alternatively, our findings and the discrepancies with the study of Martinez-Sobrido et al. (2006) might be explained if one assumes that double-stranded RNA and Lassa virus RNA are not recognized via the same intracellular receptor, with Lassa virus antagonizing its own recognition, but not that of double-stranded RNA.
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ACKNOWLEDGEMENTS |
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Received 1 September 2006;
accepted 10 January 2007.
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