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Molecular Virology Laboratory, Department of Medical Microbiology, Center of Infectious Diseases, Leiden University Medical Center, E4P, PO Box 9600, 2300 RC Leiden, The Netherlands
Correspondence
Willy J. M. Spaan
w.j.m.spaan{at}lumc.nl
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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These authors contributed equally to this work. 
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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; van der Hoek et al., 2004). Its genome consists of single-stranded RNA of positive polarity and encompasses more than 31 000 nt. Having such large genomes – and nearly all of it devoted to coding capacity – gives coronaviruses adaptive advantages compared with other viruses with smaller RNA genomes. MHV genome expression starts with the translation of two large open reading frames (ORF), which encode two polyproteins that are subsequently processed by viral proteinases into at least 16 non-structural proteins. These include an RNA-dependent RNA polymerase, three proteinases, a helicase and a number of RNA-processing enzymes (Snijder et al., 2003). The other ORFs, which are located at the 3'-third of the genome, are expressed from subgenomic RNAs. Most of these ORFs encode proteins that constitute the viral particles. The function of the majority of the viral proteins and their interaction with the host cell have not yet been fully characterized.
Coronavirus infection of established cell lines – including fibroblast cell lines – has been extensively used as a model for studying viral genome expression and virus–host interaction. During lytic MHV infection, levels of virus-encoded intracellular mRNAs rapidly increase and they actively compete for ribosomes with cellular mRNAs (Hilton et al., 1986). In this way MHV downregulates host cell translation, without having any pronounced effect on cellular transcription (Siddell et al., 1981). Like other positive-stranded RNA viruses, MHV uses cellular membranes as sites of viral RNA replication (van der Meer et al., 1999; Shi et al., 1999). Viral infection triggers the formation of double-membrane vesicles, which originate from intracellular membranes (Gosert et al., 2002; Prentice et al., 2004; Shi et al., 1999; van der Meer et al., 1999). Cell surface expression of the viral spike glycoprotein results in cell-to-cell fusion (Vennema et al., 1990), which is accompanied by fragmentation and rearrangement of the Golgi apparatus (Lavi et al., 1996). Accumulation of intracellular complexes of spike and the MHV receptor Ceacam1 has been implemented in the development of a cytopathic effect (CPE) (Rao & Gallagher, 1998). Profound effects of MHV infection on cellular functions and structure eventually result in cell death.
In response to viral infection, cells produce cytokines and chemokines (Li et al., 2004; Rempel et al., 2005), which play a key role in modulating innate as well as adaptive immune responses. In addition to an inflammatory response, other changes of host cell expression during MHV infection have been described previously (Cai et al., 2003; Kyuwa et al., 1994; Ning et al., 2003a, b); yet the understanding of MHV–host interactions on the cellular level has been limited.
Here, we applied microarray analysis to assess global changes in cellular expression profiles during acute cytopathic coronavirus infection. We demonstrate that MHV infection in fibroblast-like cells triggers very few changes in cellular mRNA levels in the first hours of infection. After having established exponential virus production, innate immune and inflammatory responses were elicited together with other cellular changes associated with RNA and protein metabolism, oxidative stress, cell cycle and apoptosis. The analysis of transcriptional changes in cells undergoing lytic MHV infection provides new clues into coronavirus–host interaction.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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) were grown as monolayers in Dulbecco's modified Eagle's medium supplemented with 100 U penicillin ml–1, 100 µg streptomycin ml–1 and 10 % fetal calf serum (FCS) (growth medium). After infection or during poly (I : C) treatment, cells were incubated in the same medium with antibiotics but with 3 % FCS (supporting medium). Strain A59 of MHV was obtained from ATCC. The working stock of the virus was prepared using Sac(–) cells as described previously (Spaan et al., 1981). Viral titres in p.f.u. ml–1 were determined by plaque assay on L cells (Spaan et al., 1981).
Viral infection and RNA isolation.
L cells were seeded at 7.5x105 into plates of 5 cm diameter. The next day subconfluent monolayers were washed once with PBS containing 40 µg DEAE-dextran ml–1 and incubated for 1 h at 37 °C with PBS containing 40 µg DEAE-dextran ml–1, 2 % FCS and MHV-A59 at an m.o.i. of 10. Mock-infected cells were treated in the same way with the omission of virus. After adsorption, the inoculum was removed, cells were washed twice, supporting medium was added and cells were incubated at 37 °C. In order to reduce the effect of biological variation in cellular gene expression, we performed two independent infection experiments for microarray analysis with a 3 week interval. For the two experiments, we used the same batches of all solutions, the same cell passage and the same viral stock and strove to reproduce identical conditions. Medium for virus titration and cells for RNA isolation were harvested at the indicated time points. Total RNA was isolated from the cells using TRIzol reagent (Gibco-BRL) as recommended by the manufacturer. RNA concentration was determined spectrophotometrically. For quality and quantity control, 4 µg total RNA was subjected to electrophoresis in 1 % native agarose gel and stained with ethidium bromide.
Sample preparation and chip hybridization.
Samples for hybridization to microarrays were prepared from total cellular RNA of MHV- [at 3, 5 and 6 h post-infection (p.i.)] and mock-infected (at 3 and 5 h p.i.) cells according to the Affymetrix GeneChip manual. Briefly, RNA was purified on RNeasy columns (Qiagen). A total of 12 µg RNA eluted from the columns was used for cDNA synthesis with SuperScript II reverse transcriptase (Invitrogen) and a primer containing a T7 RNA polymerase promoter site with a 5'-stretch of (dT)24. Second strand cDNA was synthesized in the presence of Escherichia coli DNA polymerase I, DNA ligase and RNase H (all enzymes from Invitrogen). Half of the dsDNA served as a template for cRNA synthesis that was performed with T7 RNA polymerase (Ambion), 100 mM of each NTP and 10 mM of each biotin-11-CTP and biotin-16-UTP (PerkinElmer). In vitro transcription yielded 15- to 20-fold amplification of the starting amount of RNA. RNA was purified on RNeasy columns and fragmented. Hybridization of RNA to Affymetrix murine GeneChip U74Av2, staining and scanning was performed in the Leiden Genome Technology Center following the manufacturer's recommendations.
Chip data analysis.
Affymetrix murine GeneChip U74Av2 has probe sets for 12 422 characterized genes and expressed sequences. Each sequence is represented by 16 probe oligonucleotide pairs, one oligonucleotide of the pair being a perfect match for the sequence and another having a single mismatch. The microarray scanning data were analysed with the use of Rosetta Resolver software, version 5.0 (Rosetta Inpharmatics LLC) according to its manual. Rosetta Resolver uses intensity signals of perfect match and mismatch probes and of background to calculate a P-value that reflects the level of confidence that a sequence is expressed. Ten transcriptional profiles of virus- and mock-infected cells were subjected to two-dimensional clustering. Normalization for clustering was achieved by transformation of intensity values into z-scores to emphasize the relative change of intensity of a gene across transcriptional profiles. An agglomerative clustering algorithm, error-weighted Cosine correlation as a similarity measure for profiles and genes, a complete linkage method for profiles and mean linkage method for genes were applied for clustering. A total of 938 gene clusters with the coefficient of variation more than 0.3 were included. In order to identify sequences with virus-induced changes in the expression level, we compared profiles of infected cells at 3 and 5 h p.i. with corresponding profiles of mock-infected cells. Profiles of MHV-infected cells at 6 h p.i. were compared with those of mock-infected at 5 h p.i. Combined replicate profiles from two independent experiments were used in the above comparisons. A positive fold-induction is the ratio of sequence intensity values in infection and mock-infection profiles. A negative fold-induction is the reverse ratio (mock- to MHV-infection) with the minus sign. The P-value of the ratio takes into account differences in intensities of infected and control probe sets as well as intensity variance within each probe set and reflects the confidence of differential expression. For all analyses we set the P-value to be less than 0.01.
Sequences that showed differential expression in infected cells were grouped according to Gene Ontology terms of biological processes or cellular components, which were available on the website of the National Center for Biotechnology Information in March, 2005. Sequences not yet annotated by Gene Ontology were not analysed further. Genes that could be placed into more than one group according to their annotation, were put arbitrarily into a single group. Here, we present differentially expressed genes that belong to the selected 14 groups and that were significantly changed by 2.5-fold or more (P-value<0.01). We used gene symbols defined by the rules of the International Committee on Standardized Genetic Nomenclature for Mice (http://www.informatics.jax.org/mgihome/nomen/gene.shtml).
Quantitative RT-PCR.
cDNA was synthesized with 1 µg total cellular RNA as template, 0.5 µg random hexamers (Promega) and SuperScript II reverse transcriptase (Invitrogen). Random hexamers were chosen as primers in order to represent the relative amount of each RNA species in the cells. Aliquots of the same cDNA solution were used for quantitative PCR (qPCR) on different templates. Gene-specific primers (nucleotide sequences are available on request) for qPCR were selected with the help of Primer3 software (Rozen & Skaletsky, 2000). A primer set for the MHV-A59 3'-untranslated region, annealing to genome-length and subgenomic viral RNA, was used for the detection of total viral RNA. Primers for MHV-A59 ORF1b were used for the detection of genome-length viral RNA. qPCR was performed with HotStar Taq polymerase (Qiagen) and SYBR Green I (Molecular Probes) in an iCycler PCR machine (Bio-Rad) for 40 cycles with three steps in a cycle, each step for 20 s, a denaturing step at 94 °C, an annealing step at a temperature specific for a given pair of primers (58–63 °C) and an extension step at 72 °C. Data were analysed with iCycler software. Specificity of qPCR was confirmed by the melting curve of amplified products. Ten-fold dilutions of a cDNA sample with the highest concentration of a given template were used to build standard curves. In a similar way, standard curves for total and genome-length viral RNA were built using cDNA of a mixture of 0.9 µg total RNA from uninfected cells and 0.1 µg virion RNA. Virion RNA was isolated from virions purified by isokinetic sedimentation in a sucrose gradient as described before (Spaan et al., 1981). The amount of RNA in a sample was determined with respect to a standard sample and expressed in relative units. Results of quantification were normalized to the amount of Gapdh mRNA in the same sample in order to correct for efficiency of reverse transcription. Finally, results were arbitrarily normalized to fit a convenient scale. Each qPCR was performed in triplicate, means and standard deviation (SD) were calculated. The level of interferon 
4 and 
(Ifna4 and Ifnb) mRNA in infected and mock-infected cells was below the detection limit. Ifn fold-induction after poly (I : C) treatment was calculated as a ratio of the IFN RNA level at a given time point and the detection limit.
Ifn induction by poly (I : C).
L cells were seeded as for an infection experiment. The next day cells were washed with PBS and incubated for 2 h at 37 °C in supporting medium containing 400 µg DEAE-dextran ml–1. After that, cells were washed with PBS and incubated for 32 h at 37 °C in supporting medium with 100 µg poly (I : C) ml–1 (Sigma). At the indicated time after poly (I : C) addition, cells were dissolved in TRIzol for total cellular RNA isolation.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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). In order to be able to correlate changes in cellular expression with parameters of viral infection, we determined the kinetics of virus production, viral RNA content and CPE development in L cells that are maintained in our lab. We used an m.o.i. of 10 in order to infect all cells simultaneously. During the first 4 h p.i., no visible changes in the cell morphology were observed and no virus was secreted into the medium (Fig. 1a). The end of the lag period and the beginning of the exponential phase of virus production coincided with the appearance of CPE, i.e. the formation of multinuclear giant cells, at 5 h p.i. Viral production reached a maximum level at 9 h p.i. when nearly all cells were fused into syncytia. At this stage virus yield was 1000 p.f.u. cell–1 (Fig. 1a). The use of a sensitive RT-qPCR allowed us to measure the levels of viral RNA from the beginning of infection. The increase of viral RNA levels preceded that of viral production by 2 h (Fig. 1b). With a 1 h interval between time points, the accumulation of both genome-length and subgenomic RNA started simultaneously at 2 h p.i. The molar ratio of total viral RNA to genome-size viral RNA reached 10 : 1 at 4 h p.i. Later in infection this ratio remained constant, which was similar to that described for bovine coronavirus infection (Hofmann et al., 1990).
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). We chose 3, 5 and 6 h p.i. as time points for expression profiling. At 3 h p.i., the concentration of viral products within infected cells was apparently sufficient to support exponential viral RNA accumulation, but there was no virus secretion and no obvious CPE yet. At 5 and 6 h p.i., viral production was in the exponential phase. The levels of viral RNA increased by 100-fold (genome-size) and 200-fold (total) at 5 h p.i. as compared with 3 h p.i. Multinuclear cells started to appear at 5 h p.i. and harboured approximately 25 % of the nuclei at 6 h p.i. Expression profiles in mock-infected cells at 3 and 5 h p.i. served as controls.
Overall cellular gene expression during MHV infection
Approximately 44–48 % of 12 422 sequences represented on the chips were expressed in mock-infected L cells and early in infection. Later in infection the number of expressed genes decreased to 41 and 38 % at 5 and 6 h p.i., respectively. Clustering analysis allowed us to visualize differences in cellular gene expression. Profiles of infected L cells at 3 h p.i. clustered together with those of mock-infected cells, which indicated a very low impact of viral infection on the steady-state levels of cellular RNAs at this time point (Fig. 2). A pronounced effect of infection became obvious at 5 and especially 6 h p.i. (Fig. 2). Clustering illustrated biological variance in two independent experiments. Despite our attempts to reproduce the experimental conditions, profiles of mock-infected cells and of MHV-infected cells at 3 h p.i. formed two separate clusters according to the experiment (Fig. 2). Combining two replicates for further analysis increased the statistical significance of the analysis and filtered out non-consistent changes that were present only in one experiment. Reliability of the analysis was confirmed further by the consistency of many changes throughout the course of infection (see Tables 1–4).
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, inset tables). Levels of Fos and Cxcl2 transcripts increased, B2m and Nono transcript content dropped (Fig. 3), and Ifnb and Ifna4 mRNA was undetectable during MHV infection (data not shown).
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) that belonged to selected groups and had more than 2.5-fold changes in expression in comparison with control samples.
Innate immunity, inflammatory and defence responses, and signalling.
MHV infection in L cells resulted in an induction of three inflammatory chemokines: Cxcl1, Cxcl2 and Cx3cl1 (Table 1). An increase in Cxcl2 RNA concentration was detected at 3 h p.i. and reached a sevenfold increase at 6 h p.i. Cxcl1 and Cxcl2 are immediate-early chemokines that attract neutrophils to sites of injury in vivo. Cx3cl1 functions as a chemokine as well as an adhesion molecule. Together with Cxcl1 and Cxcl2, induction of interleukin-6 (Il6) and tumour necrosis factor alpha (Tnfa) mRNA were found to be prominent responses to MHV infection in neural cells (Rempel et al., 2005). However, MHV did not induce expression of Il6 and Tnfa in L cells. Differences in cytokine expression patterns between MHV-infected neural and fibroblast-like cells suggest different mechanisms of induction of these cytokines. An anti-inflammatory response in virus-infected L cells was illustrated by suppression of Jak3 and elevation of suppressor of cytokine signalling 3 (Socs3) expression (Table 1).
Despite the fact that L cells were able to sense the viral infection and respond to it with chemokine induction, the interferon pathway was not activated at any time point during MHV infection. The absence of transcripts of immediate-early interferons (Ifna4 and Ifnb) was confirmed by RT-qPCR (data not shown). In order to exclude the possibility that our line of L cells had a defect in the interferon induction pathway, we treated the cells with a known interferon inducer, poly (I : C). Immediate-early Ifns mRNA levels increased more than 10-fold after 3 h of treatment (Fig. 4). Maximum induction of approximately 1000-fold was achieved at 22 h. Induction was also obtained with Sendai virus infection in L cells (data not shown). It was shown previously that various strains of MHV, including A59, are poor inducers of interferon in cultured cells (Garlinghouse et al., 1984; Sturman & Takemoto, 1972). Whether MHV hides from recognition by the interferon induction system or actively suppresses it remains a question for future research.
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) that present intracellular antigens to specialized immune cells. Tripeptidyl peptidase II (Tpp2), which plays a crucial role in MHC-I presentation (Reits et al., 2004), was also downregulated (Table 3). Reduction in mRNA levels and surface expression of MHC-I was found previously in a macrophage cell line infected with MHV (Kyuwa et al., 1994). However, in non-lytically infected cells MHC-I has been shown to be upregulated, probably by paracrine action (Lavi et al., 1989; Rempel et al., 2005). Mouse cells ubiquitously express Crry, a cell surface-bound complement regulatory protein, capable of inhibiting C3 convertase activity and thereby protecting cells from homologous complement (Nomura et al., 2002). RNA levels for this gene were greatly reduced in MHV-infected cells (Table 1), potentially rendering infected cells vulnerable to destructive complement action.
MHV infection affected expression of a number of genes associated with signalling cascades that regulate homeostasis, growth, differentiation, response to stress and death. Mapk signalling mediates inflammatory responses and it might be involved in induction of the chemokines described above. Dual specificity phosphatases (Dusp) modulate intracellular signalling by dephosporylation of Mapks thus limiting an inflammatory reaction. During MHV infection, Dusp1, 2 and 8 were upregulated (Table 1). This result supports the observation that both inflammatory and anti-inflammatory signals were activated in MHV-infected cells.
RNA metabolism.
The largest group of genes differentially expressed in MHV-infected cells was associated with cellular transcription. In this group, transcription factor Fos showed the strongest induction. Fos, as well as Jun, Junb and Egr1 (Krox-24), which were also upregulated in infected cells (Table 2), are induced in response to diverse signals. These transcription cofactors initiate ordered expression of target genes thus regulating cell division, apoptosis and inflammatory responses. Fos, Jun and Junb are constituents of the activator protein-1 (AP-1) transcription factor complex that was shown to play a key role in the induction of IL-8 by the spike glycoprotein of SARS-CoV (Chang et al., 2004). In the same way, upregulation of AP-1 genes in MHV-infected mouse cells could lead to an induction of chemokine Cxcl2, a mouse functional counterpart of human IL-8. On the other hand, downregulation of some other transcription factors implied suppressive action of the virus. Activation of Nfkb (NF-
B) by its release from a complex with inhibitor Nfkbia (IB) or by transcriptional induction is a common feature of a response to pathogens (Jenner & Young, 2005). However, in MHV-A59-infected L cells, the level of Nfkb mRNA was decreasing (–2.3-fold at 6 h p.i.), while its inhibitor Nfkbia was induced (Table 2).
Differentially expressed genes participating in RNA processing and splicing and in export of RNA from the nucleus were prevalently downregulated (Table 2). The earliest change in expression in the RNA metabolism group was detected for the Nono gene that was downregulated from 3 h p.i. onwards (Table 2). Nono in complex with proline/glutamine-rich splicing factor Sfpq, the expression of which was also downregulated, participates in a variety of nuclear processes including transcription and pre-mRNA processing (Shav-Tal & Zipori, 2002). The finding that the human homologue of Nono constantly shuttles between the nucleus and cytoplasm (Zolotukhin et al., 2003) suggested that this protein may also have a cytoplasmic function.
Protein metabolism.
Infection by various viruses results in endoplasmic reticulum (ER) stress that can be caused by either synthesis of proteins foreign to the host cells (Dimcheff et al., 2004) or rapid accumulation of substantial amounts of viral, especially misfolded, proteins in the ER (Li et al., 2005; Netherton et al., 2004; Su et al., 2002). MHV replication in its exponential phase led to induction of three genes that are considered to be key markers of the unfolded protein response: homocysteine-responsive endoplasmic reticulum resident protein 1 (Herpud1 or Herp), DNA-damage inducible transcript 3 (Ddit3 or Chop) (Table 3) and heat shock 70 kDa protein 5 (Hspa5 or Bip; 1.5-fold at 6 h p.i.).
A number of genes encoding ubiquitin-specific proteases (Usp) were downregulated in infected cells (Table 3). Suppression of Usp genes could indicate enhanced ubiquitin-mediated protein degradation as part of the unfolded protein response and could also affect other possible functions of Usps, such as regulation of transcription, membrane protein trafficking and signal transduction (Amerik & Hochstrasser, 2004). It was recently shown that coronavirus papain-like proteinase PLpro can act as a deubiquitinating enzyme (Barretto et al., 2005; Lindner et al., 2005). Knowledge of changes in the cellular environment might help in identifying the function and specificity of the virus-coded enzyme.
Oxidative stress, cell cycle, DNA repair and apoptosis.
Additional evidence for ER-overload in MHV-infected cells was supplied by detection of upregulated expression of the myeloperoxidase (Mpo) and thioredoxin interacting protein (Txnip) genes, which are characteristic for oxidative stress (Table 4). Stress conditions can eventually lead to cell cycle arrest and apoptosis. Genes with a strongly changed expression later in infection were consistent with an anti-apoptotic programme (Table 4). Caspase 7 (Casp7) and death-associated kinase 3 (Dapk3) (Kawai et al., 1998) participate in the induction of apoptosis and their mRNA levels were significantly decreased in infected cells. Other genes involved in apoptosis had smaller changes in expression. Taken together, both pro- as well as anti-apoptotic genes were differentially expressed as a result of lytic infection. The overall effect on the induction of apoptosis in coronavirus-infected L cells remains yet inconclusive.
Concluding remarks
We applied microarray analysis to study changes in the steady-state levels of cellular mRNAs during a one-step growth curve of MHV. Viral infection can influence the transcriptional profile of infected cells by affecting rates of mRNA synthesis and processing, transport from the nucleus to cytoplasm, and decay in the cytoplasm. Coronavirus proteins including RNA modifying enzymes (Snijder et al., 2003) and proteinases can act directly on cellular mRNA or on cellular enzymes involved in RNA metabolism. In addition, transcript levels can be modulated as a cellular response to viral products. Ongoing improvement of nucleotide sequence annotations and microarray analysis tools might support new findings in the same datasets. Future studies are needed to reveal whether protein levels of the differentially expressed genes are also changed in MHV-infected cells and what role these proteins play in coronavirus replication.
Recently, Rempel et al. (2005) reported microarray analysis of primary culture of a mixed population of neural cells infected with MHV. Infection in the neural culture was slow and non-lytic with only 10 % of the cells infected by JHM strain of MHV at the time of transcription profiling on day 3 p.i. (Rempel et al., 2005). Interestingly, despite big differences in experimental setup, some cellular genes showed the same trends in expression in two different models of MHV–host interaction. Among the common responses were upregulated genes encoding chemokines, Junb and Nfkbia. Probably, mechanisms of induction of these genes are common for these two models and can therefore be conveniently studied in an established cell line in the future. The relatively small overlap of two expression datasets from neural and fibroblast-like cells can be explained by reasoning that the majority of differentially expressed genes in the primary neural culture represented paracrine effects – changes in uninfected cells that constituted 90 % of the cells in the culture.
In the course of MHV infection in L cells, chemokine induction became gradually more prominent. In contrast to chemokine induction, no increase in mRNA levels of interferons or any of their known downstream effectors was detected at any of the time points investigated. These data are in agreement with the long-standing observation that many coronavirus strains are sensitive to interferon pre-treatment, but poor interferon inducers in infected cells (Aurisicchio et al., 2000; Garlinghouse et al., 1984; Matsuyama et al., 2000; Taguchi & Siddell, 1985; Virelizier & Gresser, 1978). Recently, Spiegel et al. (2005) concluded that SARS-CoV interferes with the key transcription factor, interferon regulatory factor 3 (IRF-3), involved in interferon induction, which suggests that interferon response can be counteracted by a coronavirus-encoded antagonist as has previously been described for several other (+) RNA-containing viruses (Frolova et al., 2002; van Pesch et al., 2001; Zoll et al., 2002).
Our analysis provided data on the cellular environment of coronavirus replication. On the basis of our current knowledge of the strategy of coronavirus genome expression, some of the genes with changed expression (Nono, Sfpq, Usps) might play a direct role in the viral life cycle. Genes encoding chemokines, constituents of transcription factor complex AP-1, proteins involved in stress responses (to unfolded protein and oxidative stress) are likely to represent cellular responses to viral infection. Newly identified cellular genes from either group can serve as potential targets for the development of antivirals if these responses are common to coronavirus infections. Current research in our laboratory is aimed at identification of differences in expression profiles between acutely and persistently infected cells as well as unravelling of induction mechanisms of the chemokine responses described in this work.
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ACKNOWLEDGEMENTS |
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Received 9 December 2005;
accepted 2 March 2006.
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) and genome-size viral RNA (
) are shown.
) cells. mRNA content in the cells was determined with the use of RT-qPCR and expressed in relative units (RU). Inset tables show fold-induction as determined by hybridization to microarrays (MA) and by RT-qPCR (qPCR). Microarray data for Nono are from two probe sets. Values marked with an asterisk had a P-value more than 0.01.
) mRNA in L cells by poly (I : C) treatment. L cells were pre-treated for 2 h with DEAE-dextran and at time point 0 h100 µg poly (I : C) ml–1 was added. Ifn RNA content was determined by RT-qPCR and fold induction was calculated as described in Methods.