Specific and common changes in Nicotiana benthamiana gene expression in response to infection by enveloped viruses

G. Senthil1, H. Liu2, V. G. Puram3, A. Clark1, A. Stromberg2 and M. M. Goodin1

1 201F Plant Science Building, Department of Plant Pathology, University of Kentucky, Lexington, KY 40546, USA
2 Department of Statistics, University of Kentucky, Lexington, KY 40506, USA
3 Advanced Genetics Technologies Center (AGTC), University of Kentucky, Lexington, KY 40546, USA

Correspondence
M. M. Goodin
mgoodin{at}uky.edu


   ABSTRACT
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
 
Microarrays derived from Solanum tuberosum expressed sequence tags were used to test the hypothesis that genetically distinct enveloped viruses elicit unique changes in Nicotiana benthamiana gene expression. The results of our study, which included Sonchus yellow net virus (SYNV), a plant rhabdovirus that replicates in the nucleus of infected cells, and Impatiens necrotic spot virus (INSV), a plant bunyavirus that replicates in the cytoplasm, were consistent with this hypothesis. Statistically significant changes (P<=0·01) in the expression of 275, 2646 and 4165 genes were detected in response to INSV at 2, 4 and 5 days post-inoculation (d.p.i.), respectively. In contrast, 35, 665 and 1458 genes were expressed differentially in response to SYNV at 5, 11 and 14 d.p.i., respectively. The microarray results were verified by Northern hybridization using a subset of these genes as probes. Notably, INSV, but not SYNV, induced expression of small heat-shock protein genes to high levels. In contrast to SYNV, infection by INSV resulted in downregulation of all histone genes, of which the downregulation of histone 2b expression to very low levels was confirmed by Northern hybridization. The expression of a putative WRKY transcription factor at 11 d.p.i., but not at 5 or 14 d.p.i., in SYNV-infected tissue suggested that the temporal response to virus infection was identified readily using our experimental design. Overall, infection by INSV resulted in larger fold changes in host gene expression relative to infection by SYNV. Taken together, the present data demonstrate differential responses of a common host to two genetically distinct viruses.

Raw microarray data and more comprehensive lists of the Gene Ontology results are available as supplementary material in JGV Online.


   INTRODUCTION
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
 
Details of the factors that underlie establishment of successful virus infections of plants by influencing virus replication and movement or suppression of plant defences remain poorly understood in plant virology (Maule et al., 2002). Despite advances that have been made in identifying changes in plant gene expression in response to infection by plus-strand RNA viruses, similar studies have not been conducted with viruses with monopartite, negative-strand RNA genomes, such as Sonchus yellow net virus (SYNV), a member of the genus Nucleorhabdovirus (Jackson & Christie, 1977). Rhabdoviruses with animal hosts are known to shut off host gene expression and repress promoter activity (Weck & Wagner, 1978; Ahmed & Lyles, 1997). However, a similar activity has not been described for plant-infecting rhabdoviruses. If such activity is conserved, infection by these viruses should result in a highly modulated effect on host gene expression compared with viruses that are known inducers of host gene expression. We tested this hypothesis by conducting a comparative microarray study to examine changes in plant gene expression in response to infection by SYNV and Impatiens necrotic spot virus (INSV). Of the model host plants available for such studies, Nicotiana benthamiana supports the replication of both INSV and SYNV, in contrast to Arabidopsis thaliana, which does not support replication of SYNV (M. M. Goodin, unpublished data). Furthermore, the advent of facile methods for high-throughput gene silencing (Lu et al., 2003) and facile expression of fluorescent protein fusions by agroinfiltration or viral vectors for protein-localization studies (Bendahmane et al., 2000; Goodin et al., 2002; Escobar et al., 2003) make N. benthamiana an increasingly attractive host for functional genomics studies. In lieu of microarrays containing N. benthamiana gene sequences, we have successfully employed heterologous arrays derived from expressed sequence tags (ESTs) of Solanum tuberosum, a closely related member of the family Solanaceae (D'Arcy, 1979; Ronning et al., 2003).

SYNV, an aphid- and mechanically transmissible virus, replicates and undergoes morphogenesis in the nuclei of infected plant cells (Jackson et al., 1987; Martins et al., 1998). The SYNV genome is encoded by a single segment of negative-stranded RNA of 13 720 nt in length (Heaton et al., 1989). In contrast to SYNV, INSV is a thrips- and mechanically transmissible plant bunyavirus that replicates and undergoes morphogenesis in the cytoplasm of infected cells. The spherical particles of INSV contain the viral genome, which is divided into three segments of negative- or ambisense single-stranded RNA, designated S (2922 nt), M (4972 nt) and L (8776 nt) (Law et al., 1992; van Poelwijk et al., 1996). Given the contrasting genetics of SYNV and INSV, their use in microarray-based experiments may provide a stringent test of the hypothesis that genetically distinct RNA viruses may induce the expression of common sets of genes in susceptible plants (Golem & Culver, 2003; Whitham et al., 2003). Furthermore, such genetic diversity should result in markedly different changes in plant gene expression compared with that observed for plus-strand RNA viruses (Golem & Culver, 2003; Whitham et al., 2003).


   METHODS
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
 
Plant growth, viral inoculation and detection.
N. benthamiana plants were maintained in a greenhouse with a 14 h photoperiod and at a constant temperature of 25 °C. Plants were inoculated when they had four to six fully expanded leaves (approx. 4 weeks after planting). Viral inoculum was prepared from systemically infected leaves of SYNV- or INSV-infected plants. Approximately 1 g infected leaf tissue, harvested immediately before use, was homogenized in 10 ml inoculation buffer (10 mM phosphate, 0·5 % NaSO3, 1 % Celite, pH 6·9). Inoculum was applied to the lower three leaves of N. benthamiana plants by rub-inoculating with a latex-gloved finger. The youngest fully expanded, systemically infected leaves were harvested at three different time points after inoculation. For SYNV-infected plants, leaves were collected at 5, 11 and 14 days post-inoculation (d.p.i.), and for INSV-infected plants, the leaf tissue was harvested at 2, 4 and 5 d.p.i. Control plants were mock-inoculated with extracts from healthy leaves ground in inoculation buffer and the leaves were harvested at the same time points as the infected plants. Harvested leaf tissue was frozen immediately in liquid nitrogen and then stored at –85 °C until RNA extractions were conducted. Pools of RNA isolated from mock- and virus-infected leaves were screened by RT-PCR to ensure that RNA from mock-inoculated plants was not contaminated and that virus-inoculated plants were indeed infected. Oligonucleotide primers designed to amplify the 5' 917 nt of the SYNV nucleocapsid (N) gene (GenBank accession no. M17210) or the entire 789 nt of the INSV N gene (GenBank accession no. D00914) were used. Template RNA was reverse-transcribed into cDNA (Superscript II; Invitrogen) prior to PCR amplification using Dynazyme EXT thermostable DNA polymerase (MJ Research).

Experimental design.
To average out differences in gene expression due to plant-to-plant variation, RNA was isolated from leaves collected from a group of five plants and pooled. Tissue from two or three replicate sets was harvested for each time point for experiments conducted with INSV or SYNV. In turn, for each RNA sample, two array hybridizations were conducted on independent arrays, with one of the arrays being hybridized with reciprocally labelled cDNA samples as described below. Therefore, a total of six hybridizations were performed for each time point using RNA isolated from SYNV-infected plants. Four hybridizations per time point were conducted using INSV samples. In addition to evaluating variation among sets of plants, this experimental design permitted determination of the effect of each fluorescent dye on hybridization efficiency, as well as the reproducibility of the hybridizations. Independent sets of plants grown at different times were used for microarray and Northern hybridizations to validate the differential expression.

Potato cDNA microarray.
Potato (S. tuberosum) cDNA microarrays were obtained from The Institute of Genomic Research (TIGR). These microarrays consist of 15 264 ESTs derived from potato cDNA libraries (Ronning et al., 2003; www.tigr.org/tdb/potato) spotted in duplicate on Corning UltraGaps Slides (Corning Incorporated). The sequences of these ESTs can be accessed through the TIGR website and GenBank.

RNA extraction, fluorescent labelling and microarray hybridization.
Total RNA was extracted from the leaf tissue by using an RNeasy Plant kit (Qiagen) according to the manufacturer's instructions. cDNA synthesis, labelling of cDNA with Cy3 and Cy5 fluorescent dyes and microarray hybridizations were performed by using a 3DNA Submicro EX Expression Detection kit (Genisphere) following the manufacturer's protocol. Total RNA (5 µg) from virus-infected and healthy leaves was reverse-transcribed to cDNA for each array. For each time point, reciprocal labelling was performed to ensure that our results were not biased by dye effects.

Microarray processing, data analysis and hierarchical clustering.
Following post-hybridization washes, microarrays were scanned by using a ScanArray Express 4000 confocal laser scanner (Perkin-Elmer). Data acquisition and quantification of spot intensities were performed by using the ScanArray Express Microarray analysis system, version 2.0 (Perkin-Elmer). The foreground and background fluorescence intensities for each spot were calculated by using the adaptive-circle segmentation protocol included in the ScanArray software. The median signal intensity of each spot was obtained by subtracting the local median background intensity from the median intensity of each spot. To eliminate the spatial and intensity variations within a slide, the LOWESS normalization method was applied to the median spot intensities of images generated from either channel 1 (Cy5) or channel 2 (Cy3). Prior to statistical analysis, the datasets were filtered to exclude data points if they did not meet the following criteria across all replicates: (i) if the normalized median spot intensities were zero or <200 (pixel intensity), (ii) if the spot was determined to be unusable as defined by criteria in the ScanArray Express software or (iii) if the median foreground intensity was <20 % of the median background intensity. As each EST sequence was duplicated on the slide, a mean intensity of the two spots was used for statistical analysis. Preliminary analysis of dye-swap experiments did not suggest a significant dye effect and, hence, they were considered as replicates in subsequent statistical analyses. The filtered data were used to identify the differentially regulated genes by calculating the log2 ratios, where the normalized median intensity values of virus-treated samples were divided by similar values from control samples (Cy5-infected/Cy3-control or Cy3-infected/Cy5-control in a dye-swap experiment). The fold changes of differentially regulated genes in virus-infected samples compared with the control samples were calculated based on these ratios. The log2 ratios were analysed by a one-sample t-test to detect significant differences in gene expression at each time point. The EST sequences that showed differential expression with P values of <=0·01 were considered statistically significant. The expression profiles resulting from different treatments were grouped based on similarity in pattern of their expression by using hierarchical cluster analysis based on the Pearson correlation by GeneSpring version 6.1 software (Silicon Genetics). Reliability of the microarray data was estimated by calculating correlation coefficients based on the Pearson correlation.

Northern hybridization analysis.
Northern hybridization analysis was performed by using 15 µg total RNA derived from sets of plants independent of those used for microarray experiments. Following separation on 1·2 % denaturing agarose gels containing 2·2 M formaldehyde, RNA was transferred to a Hybond-N+ nylon membrane (Amersham Biosciences) by capillary blotting (Maniatis et al., 1982). Probes for hybridization were generated by PCR amplification of N. benthamiana cDNA using primers designed based on the potato EST sequence. DNA sequencing confirmed the authenticity of the amplified DNA fragments. The PCR fragments were labelled with [{alpha}-32P]dCTP by using a RediPrime random primer-labelling kit (Amersham Biosciences) following the manufacturer's instructions. Membranes were hybridized overnight in Ultrahyb solution (Ambion) at 42 °C. Membranes were washed twice with a solution containing 2x SSC and 0·1 % SDS for 5 min at room temperature, then twice with a solution of 0·1x SSC and 0·1 % SDS for 15 min at 68 °C. The Northern blots were exposed to a phosphorimager screen and the images were visualized with ImageQuant software (Molecular Dynamics). Each probe cDNA was tested at least twice, using independent samples of RNA.

Functional categories.
Functional categorization was conducted according to Gene Ontology (GO) guidelines (Martin et al., 2004; Lewis, 2005). Following statistical analysis of the array hybridization data, ESTs of interest were grouped into lists that were (i) commonly expressed in response to INSV and SYNV or (ii) specifically up- or downregulated in response to these viruses. The sequences of these ESTs were obtained from the TIGR website (www.tigr.org). GO was used for functional classification of the differentially expressed ESTs into three categories with respect to gene function: (i) molecular function, (ii) biological process and (iii) cellular component. Prior to compilation of the ontologies, the available GO and sequence information for all solanaceous species (S. tuberosum, N. benthamiana, Nicotiana tabacum and Lycopersicon esculentum) available on the TIGR website was pooled to form a custom database. Potato EST sequences in each list were then used to find homologous matches in the custom database by using BLAST. Only ESTs with high-scoring (score value >100) BLAST comparisons (<e–4) were matched with gene names in the pooled GO database.


   RESULTS
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
 
Detection of SYNV and INSV in systemically infected leaves
The veinal chlorosis or ‘yellow netting’ associated with SYNV systemic infections first appeared at approximately 10 d.p.i. This chlorosis was followed by leaf curling, which was most prominent at 14 d.p.i. (Fig. 1b). Thereafter, symptoms in subsequent flushes of ‘recovered’ leaves were milder, even though SYNV was still detectable and mechanically transmissible up to at least 25 d.p.i. In contrast, symptoms of INSV were first detected in systemic leaves approximately 4 d.p.i. Initially, leaves developed veinal chlorosis, like SYNV, which eventually became necrotic at 5 d.p.i. By 10 d.p.i., most INSV-infected plants had wilted severely or collapsed completely (Fig. 1a). In order to permit a reasonable comparison of changes in gene expression between SYNV- and INSV-infected plants, time points for tissue collection were chosen to match the symptom severity. Therefore, tissue was collected from SYNV-infected plants at 5, 11 and 14 d.p.i., whereas that from INSV was collected at 2, 4 and 5 d.p.i. Northern blot analysis using viral N gene probes was used to assess the levels of SYNV- or INSV-specific RNAs in total RNA isolated from systemically infected leaves at the various time points (Fig. 1c). By this method, both INSV and SYNV were undetectable in 2 and 5 d.p.i. samples, respectively. The SYNV N mRNA was more abundant in 11 d.p.i. samples than in 14 d.p.i. samples. In contrast, the INSV N gene showed increased levels at 5 d.p.i. relative to 4 d.p.i. (Fig. 1c).



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Fig. 1. Symptoms and detection of SYNV and INSV in systemically infected leaves of N. benthamiana. (a) Close-up of leaves harvested for array experiments (arrow) of an SYNV-infected plant at 14 d.p.i. (b) Mock (left)- and INSV (right)-infected plants at 10 d.p.i. (c) Northern blot hybridization using SYNV- and INSV-N gene cDNAs to probe RNA samples used in microarray experiments. Total RNA isolated from systemically virus-infected leaves (I) and corresponding leaves from mock-inoculated plants (M) at different time points was used. (d) Ethidium bromide-stained gel of RNA samples used for Northern gel blot shown in (c), to demonstrate equal loading. (e) RT-PCR amplification of a 977 bp fragment of the 5' portion of the SYNV N gene or the complete N gene (789 bp) of INSV, using the same RNA as that used in microarray experiments.

 
RT-PCR analysis of the total RNA samples was carried out to confirm the presence of SYNV and INSV in systemic tissues at the times when leaves were collected (Fig. 1e). Even though SYNV and INSV were present in systemic tissues at 5 and 2 d.p.i., respectively, these plants were asymptomatic at these time points (data not shown).

Reliability of the microarray data
To assess the reliability of the microarray data, the normalized median signal intensities resulting from control samples (mock-inoculated plants) were compared across all the replicates for each treatment. A high correlation (0·90–0·95) among the healthy control samples for each time point was observed, indicating low technical and biological variation (Table 1). Variation due to differences between fluorescent dyes was calculated based on correlation coefficient between dye-swap experiments, using datasets from mock-inoculated control plants. The high correlation (0·9) observed among the dye-swap replicates indicated that dye effects were insignificant.


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Table 1. Correlation between mock-inoculated control samples at different time points

Normalized median signal intensities derived from arrays hybridized with cDNA synthesized from total RNA isolated from mock-inoculated plants were compared across all replicates for each treatment.

 
Transcriptional profiles at different time points after inoculation with SYNV and INSV
Following application of the strict criteria for accepting microarray data defined in Methods, we determined that approximately 75 % (11 383) of the 15 262 potato cDNA sequences present on the microarray hybridized to the cDNA synthesized from RNA isolated from N. benthamiana leaves. To obtain a graphical representation of changes in the global expression profiles of N. benthamiana plants infected with either SYNV or INSV, hierarchical clustering analysis was performed (Fig. 2a). From this analysis, we extracted the ESTs that were expressed differentially at each time point and presented them in an illustrative representation, using Venn diagrams to indicate the number of genes that were common or specific to each time point (Fig. 2b). From this analysis, it was evident that INSV induced a greater number of changes in gene expression than SYNV at different time points after infection (Fig. 2). Statistical analysis of the microarray data identified 275 ESTs at 2 d.p.i., 2646 ESTs at 4 d.p.i. and 4165 ESTs at 5 d.p.i. that displayed statistically significant differential expression (P<=0·01) in response to INSV infection. In contrast, expression of a relatively small number of transcripts (35 ESTs at 5 d.p.i., 665 ESTs at 11 d.p.i. and 1458 ESTs at 14 d.p.i.) changed as a consequence of SYNV infection (Fig. 2). In general, approximately equal numbers of genes were either induced or repressed at the different time points after infection by either SYNV or INSV, with the exceptions of INSV at 2 d.p.i., where more genes (204) were downregulated, and SYNV at 14 d.p.i., where more genes were upregulated than repressed.



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Fig. 2. (a) Hierarchical cluster analysis of differential expression profiles for 11 383 ESTs of N. benthamiana infected with SYNV or INSV. Only data that met the strict criteria defined in Methods are presented here. The ratio of fluorescent-dye (Cy3 and Cy5) intensity measured for each co-hybridized cDNA on the array at each time point was converted into log2 ratios for cluster analysis. The columns correspond to different time points (d.p.i.) after infection with SYNV and INSV. Gene-expression profiles are shown in rows (scale given on the left-hand side). ESTs with increased expression in virus-infected plants are shown in red. Genes that were downregulated or showed no change relative to expression in mock-inoculated plants are coloured blue or yellow, respectively. (b–e). Venn diagrams showing the relationship between genes that showed statistically significant (P<=0·01) differential expression in response to infection by SYNV or INSV. The total number of genes expressed at each time point is given in parentheses. The number of genes that were commonly expressed at different times is provided in the overlapping portions of the circles. The sum of all numbers within any given circle is the number of genes expressed differentially at that time point. (b) Relationship between the genes expressed in response to infection by INSV at 2, 4 and 5 d.p.i. (c) Relationship between the genes expressed in response to infection by SYNV at 5, 11 and 14 d.p.i. (d) Relationship between the genes expressed in response to infection by INSV at 4 d.p.i. and SYNV at 11 d.p.i. (e) Relationship between the genes expressed in response to infection by INSV at 5 d.p.i. and SYNV at 14 d.p.i.

 
Functional categorization of ESTs expressed differentially in response to INSV and SYNV
In order to organize the array data into categories of genes with similar functions, we employed the GO guidelines (Martin et al., 2004; Lewis, 2005) as described in Methods. We note here that comparable results were obtained when our datasets were categorized by using the Arabidopsis Munich Information Center for Protein Sequences (MIPS) method (unpublished data). For brevity, we report here an analysis of the expression profiles for 100 genes whose expression was (a) induced by SYNV and INSV, (b) repressed by SYNV and INSV, (c) induced by INSV only or (d) induced by SYNV only (Table 2). These genes were sufficient to reveal significant differences between the biology of these two viruses (Table 2). Most striking is the finding that the fold induction or repression of gene expression was always greater in INSV-infected tissue than in that infected by SYNV. In Table 2(a, b), the fold changes of differentially expressed genes in response to SYNV infection are lower than the corresponding response to INSV. This trend held true for the virus-specific responses presented in Table 2(c, d). Of the 25 genes that were upregulated by INSV and SYNV, seven were assigned to being involved in cell defence (Table 2a). Of the 25 genes downregulated the most by INSV and SYNV, five were histone genes (Table 2b). No other class of genes showed such coordinated downregulation. Of the 25 genes that were induced most highly by INSV, four were heat-shock protein genes (Table 2c). No particular classes of genes were induced specifically by SYNV (Table 2d). More comprehensive lists of the GO results, as well as the raw data, are provided as supplementary material in JGV Online.


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Table 2. Expression levels of differentially expressed genes from four expression categories

(a) Genes that were commonly upregulated by SYNV and INSV. (b) Genes that were commonly downregulated by SYNV and INSV. (c) Genes that were upregulated only in response to infection by INSV. (d) Genes that were upregulated only in response to infection by SYNV. Genes in bold correspond to those that were used in the Northern blots shown in this study.

 
Confirmation of array data by Northern hybridization
Whilst microarrays provide a means to determine changes in the expression of thousands of genes simultaneously in a single experiment, there is a risk of obtaining misleading results. Therefore, confirmation of microarray data by secondary methods, such as Northern hybridization or real-time (quantitative) PCR, is essential (Whitham et al., 2003; Zhong & Burns, 2003). Such supporting data were particularly important in this study, as a heterologous microarray was employed. In this study, there was a high degree of agreement between our microarray and Northern hybridization results (Figs 3 and 4).



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Fig. 3. Confirmation of microarray data by Northern hybridization. Radiolabelled DNA fragments corresponding to ESTs shown to be upregulated in response to INSV and SYNV were used as probes in Northern hybridization experiments. Northern hybridizations were performed as described in Methods, using RNA isolated from a set of plants independent of those used for array experiments. RNA isolated from mock-inoculated leaves (M) is loaded beside the corresponding RNA from virus-infected tissue (I) at 5, 11 and 14 d.p.i. (SYNV) and 2, 4 and 5 d.p.i. (INSV). (a) Genes induced by infection with SYNV or INSV. (b) Genes specifically upregulated by INSV. (c) Genes specifically induced by SYNV. (d) Control hybridization using a cDNA probe corresponding to the N. tabacum 18S RNA to demonstrate equal RNA loading. (e) Ethidium bromide-stained agarose gel showing rRNA bands of samples used to generate Northern blots in panels (a–d).

 


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Fig. 4. (a) Heat-shock protein genes are induced by INSV, but not by SYNV. Northern hybridization was used to confirm microarray results demonstrating that HSP 70, HSP 20 and HSP 18 are induced specifically by INSV, but not by SYNV. (b) Downregulation of H2b gene expression by SYNV and INSV. Confirmation by Northern hybridization showed that SYNV had a less dramatic effect than INSV on downregulation of H2b at 4 and 5 d.p.i.

 
Similar to results for tobamoviruses using microarray-based experiments (Whitham et al., 2003) and for a potyvirus using in situ hybridization (Aranda et al., 1996), INSV induced both small and large heat-shock proteins (Table 2c; Fig. 4a), a finding that was confirmed by Northern hybridization. Such a ‘heat-shock’ response was not observed in the case of SYNV infection at any time point. Interestingly, for the small heat-shock proteins HSP 18 and HSP 20, there was consistently higher expression of these genes at 4 d.p.i., with a decrease in expression at 5 d.p.i. with INSV infection.

Although we have focused primarily on identification of genes upregulated in response to virus infection, we have also confirmed the validity of microarray results for downregulated genes (Fig. 4b). As seen in Table 2(b), histone genes were downregulated in response to virus infection. The results of our Northern blots supported our array results in that only a slight downregulation of histone 2b (H2b) was observed in response to SYNV infection at 11 (–1·3-fold, P=0·02439) and 14 (–1·9-fold, P=0·00090) d.p.i. In dramatic contrast, the H2b transcript was virtually undetectable in RNA samples isolated from leaves infected with INSV at 4 (–2·5-fold, P=0·02879) or 5 (–10·5-fold, P=0·00002; Fig. 4b) d.p.i.


   DISCUSSION
Top
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
 
With this study, we report comparative changes in the transcriptional profiles that occur in systemically infected leaf tissue of N. benthamiana in response to infection by enveloped viruses. We have focused upon the effects on plant gene expression mediated by the genetically distinct viruses, namely SYNV, a minus-strand RNA nuclear-trophic virus, and INSV, an ambisense-strand RNA virus that replicates in the cytoplasm of infected cells. Given their contrasting structure, genetics and sites of replication, we used these viruses to test the hypothesis that genetically diverse enveloped viruses elicit unique changes in N. benthamiana gene expression. Understanding the transcriptional changes associated with viral infection should reveal details of how plants respond to infection by viruses (Whitham et al., 2003). It has been proposed that array-based experiments to characterize host resistance responses, so-called ‘resistome analysis’, might contribute to the quick elucidation of mechanisms that underlie defence responses to viruses (Marathe et al., 2004). Enveloped viruses remain largely understudied in these respects, despite their significant impact on agriculture (Jackson et al., 1987; Daughtrey et al., 1997; Hogenhout et al., 2003).

In addition to reporting the changes in host gene expression, we provide insight into relationship between these changes and the accumulation of viral RNAs. In the case of INSV, the accumulation of higher amounts of viral RNAs was correlated with a corresponding increase in the number of plant genes that were expressed differentially. This can be explained either by an increase in the amount of viral RNA per infected cell or by the expansion of the number of infected cells, particularly between 4 and 5 d.p.i. Neither of these two mechanisms can be ruled out at this time, particularly as no change in the ratio of the amounts of S-RNA to INSV-N mRNA was observed. In contrast to INSV, Northern blots suggested that SYNV-N mRNA was in higher abundance at 11 d.p.i. than at 14 d.p.i. (Fig. 1c). Light microscopy and immunolocalization experiments failed to detect any differences in the number of cells in systemically infected leaves at 11 and 14 d.p.i. (data not shown). Therefore, at this time, we cannot accept the hypothesis that a change in the number of infected cells was responsible for the observed results. Thus, the implications of our results are twofold. Firstly, the detection of viral mRNA in higher abundance at 11 d.p.i. suggests the possibility that most of the infecting virus particles were in the transcription stage of their replication cycle, which is an early event. It follows that genes that are upregulated at early time points of infection would be detected preferentially at 11 d.p.i. This is clearly demonstrated for probe BQ512878, an EST with homology to a WRKY4 transcription factor (Fig. 3a). These proteins comprise a major family of transcription factors that are essential in pathogen and salicylic acid responses of higher plants, as well as a variety of plant-specific reactions, and are expressed at early stages of infection (Eulgem et al., 2000). Consistent with this is the observation that genes expressed at late stages of pathogen invasion, such as chitinase, PR-1 and calmodulin (Fig. 3a), are also primarily upregulated at 14 d.p.i. On a larger scale, our Venn analyses show that only 45 % (300/665) of the ESTs that were expressed differentially at 11 d.p.i. were represented in the 14 d.p.i. dataset (Fig. 2b). Further studies are required to establish the relationship between host gene expression and the replicative status (transcription vs replication) of SYNV. Taken together, these results suggest that our present datasets accurately described the temporal changes in host gene expression in relation to the changes in SYNV gene expression.

Whilst our data agree with predictions for induced expression of plant defence genes, examination of the expression patterns for heat-shock genes revealed marked contrast between the effects of SYNV and INSV on host gene expression. As with previous reports involving potyviruses and tobamoviruses (Aranda et al., 1996; Aranda & Maule, 1998; Whitham et al., 2003), infection by INSV caused rapid induction of heat-shock genes, whereas SYNV did not (Fig. 4a). Similar to reports for tobamoviruses (Whitham et al., 2003), the induction of the small HSP genes by INSV was transient, with maximal expression at 4 d.p.i. (Fig. 4a). Whilst HSPs have been shown to play a direct role in viral transcription complexes (Qanungo et al., 2004) or defence signalling (Liu et al., 2004), such a requirement has not been established for INSV replication. To the contrary, the induction of HSP expression may reflect a generalized stress response of the plant, due to the nuclease activity of the INSV polymerase during cap snatching of plant mRNAs to produce ribonucleotide primers for transcription of viral mRNAs. This generalized stress response may also account for the downregulation of histone gene expression.

Examination of the 25 genes associated with the greatest fold changes in response to INSV or SYNV revealed an insightful trend, whereby the fold change in host gene expression in response to infection by SYNV was always lower than that for INSV (Table 2a, b). This trend was observed over the entire array for all ESTs that passed our statistical analysis (data not shown). As a difference in the number of cells that became infected by either of these two viruses was not observed, we hypothesize that infection by SYNV may result in modulation of the transcriptional response in plant cells, like their animal-infecting counterparts (Weck & Wagner, 1978; Ahmed & Lyles, 1997).

In spite of this highly modulated effect on host transcriptional profiles, we were able to identify genes that were upregulated specifically in response to infection by SYNV (Table 2d). Of particular interest is the upregulation of a subtilisin-like protease (GenBank accession no. BQ519430; P=0·00102, fold change 3·2). Further investigations will determine whether this protease is responsible for cleavage of the SYNV-N protein that is observed during late stages of infection (Jones & Jackson, 1990). Processing of the N protein has significant consequences for replication and morphogenesis of SYNV, as this protein is required in high amounts for encapsidation of full-length genomic and anti-genomic RNA molecules. Furthermore, systemic activation of such a protease may, in part, account for the ‘recovery phenotype’ characterized by reduced titre of SYNV and symptom severity in leaves produced after 14 d.p.i. We note that precedent for such proteolytic processing is established in the literature, including cleavage of the nucleocapsid proteins of human influenza viruses A and B at late stages of infection (Zhirnov et al., 1999). Additionally, we are presently characterizing antibodies raised against peptides corresponding to the termini of the SYNV N protein that detect a 21 kDa derivative in virus-infected plants (data not shown).

In addition to providing insight into the interaction of plants and enveloped viruses, we have demonstrated unequivocally that heterologous microarrays are a powerful tool for transcriptional profiling of N. benthamiana genes. Given the close genetic relatedness between species in the family Solanaceae (D'Arcy, 1979; Borisjuk et al., 1994), we hypothesized that S. tuberosum cDNA microarrays could be employed to identify changes in N. benthamiana gene expression in response to infection by lipid-enveloped plant viruses. The hybridization data shown in Figs 2, 3 and 4 support this hypothesis. Of the 15 264 unique ESTs printed on the arrays, we found that 11 383 (75 %) could hybridize to cDNA made from RNA isolated from N. benthamiana leaves. Thus, we are confident that our microarray results presented a true ‘picture’ of the effects of INSV and SYNV on host gene expression.

In conclusion, we have used heterologous microarrays to identify specific and common changes in N. benthamiana gene expression in response to infection by the enveloped viruses SYNV and INSV. Whilst these experiments provide significant insight into the biology of these viruses, future studies are expected to establish the spatial, in addition to the temporal, relationship between host gene expression and sites of virus accumulation. Moreover, when coupled with facile methods for gene silencing (Lu et al., 2003) and protein localization (Goodin et al., 2002), our results may provide the foundation for studies aimed at identifying host genes that are required for the replication and/or movement of enveloped viruses in plants. Identification of such genes may provide targets from which novel control strategies can be developed for controlling these, or related, viruses that threaten agriculture.


   ACKNOWLEDGEMENTS
 
We would like to thank Said Ghabrial, Judith Lesnaw, John Shaw and Steve Whitham for insightful discussions prior to submission. This work was funded by Tobacco Research and Development Center proposal 541201 awarded to M. M. G. Support of the AGTC was provided by US Department of Agriculture Special Grant 2002-34457-11844. This manuscript is published with the approval of the Director of the Kentucky Agricultural Experiment Station as Journal Article 04-12-119.


   REFERENCES
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
 
Ahmed, M. & Lyles, D. S. (1997). Identification of a consensus mutation in M protein of vesicular stomatitis virus from persistently infected cells that affects inhibition of host-directed gene expression. Virology 237, 378–388.[CrossRef][Medline]

Aranda, M. & Maule, A. (1998). Virus-induced host gene shutoff in animals and plants. Virology 243, 261–267.[CrossRef][Medline]

Aranda, M. A., Escaler, M., Wang, D. & Maule, A. J. (1996). Induction of HSP70 and polyubiquitin expression associated with plant virus replication. Proc Natl Acad Sci U S A 93, 15289–15293.[Abstract/Free Full Text]

Bendahmane, A., Querci, M., Kanyuka, K. & Baulcombe, D. C. (2000). Agrobacterium transient expression system as a tool for the isolation of disease resistance genes: application to the Rx2 locus in potato. Plant J 21, 73–81.[CrossRef][Medline]

Borisjuk, N., Borisjuk, L., Petjuch, G. & Hemleben, V. (1994). Comparison of nuclear ribosomal RNA genes among Solanum species and other Solanaceae. Genome 37, 271–279.[Medline]

D'Arcy, W. G. (1979). The classification of the Solanaceae. In The Biology and Taxonomy of the Solanaceae, pp. 3–47. Edited by J. G. Hawkes, R. N. Lester & A. D. Skelding. London: Academic Press.

Daughtrey, M. L., Jones, R. K., Moyer, J. W., Daub, M. E. & Baker, J. R. (1997). Tospoviruses strike the greenhouse industry: INSV has become a major pathogen on flower crops. Plant Dis 81, 1220–1230.

Escobar, N. M., Haupt, S., Thow, G., Boevink, P., Chapman, S. & Oparka, K. (2003). High-throughput viral expression of cDNA–green fluorescent protein fusions reveals novel subcellular addresses and identifies unique proteins that interact with plasmodesmata. Plant Cell 15, 1507–1523.[Abstract/Free Full Text]

Eulgem, T., Rushton, P. J., Robatzek, S. & Somssich, I. E. (2000). The WRKY superfamily of plant transcription factors. Trends Plant Sci 5, 199–206.[CrossRef][Medline]

Golem, S. & Culver, J. N. (2003). Tobacco mosaic virus induced alterations in the gene expression profile of Arabidopsis thaliana. Mol Plant Microbe Interact 16, 681–688.[Medline]

Goodin, M. M., Dietzgen, R. G., Schichnes, D., Ruzin, S. & Jackson, A. O. (2002). pGD vectors: versatile tools for the expression of green and red fluorescent protein fusions in agroinfiltrated plant leaves. Plant J 31, 375–383.[CrossRef][Medline]

Heaton, L. A., Hillman, B. I., Hunter, B. G., Zuidema, D. & Jackson, A. O. (1989). Physical map of the genome of sonchus yellow net virus, a plant rhabdovirus with six genes and conserved gene junction sequences. Proc Natl Acad Sci U S A 86, 8665–8668.[Abstract/Free Full Text]

Hogenhout, S. A., Redinbaugh, M. G. & Ammar, el-D. (2003). Plant and animal rhabdovirus host range: a bug's view. Trends Microbiol 11, 264–271.[CrossRef][Medline]

Jackson, A. O. & Christie, S. R. (1977). Purification and some physiochemical properties of sonchus yellow net virus. Virology 77, 344–355.[CrossRef][Medline]

Jackson, A. O., Francki, R. I. B. & Zuidema, D. (1987). Biology, structure and replication of plant rhabdoviruses. In The Rhabdoviruses, pp. 427–508. Edited by R. R. Wagner. New York: Plenum.

Jones, R. W. & Jackson, A. O. (1990). Replication of sonchus yellow net virus in infected protoplasts. Virology 179, 815–820.[CrossRef][Medline]

Law, M. D., Speck, J. & Moyer, J. W. (1992). The M RNA of impatiens necrotic spot Tospovirus (Bunyaviridae) has an ambisense genomic organization. Virology 188, 732–741.[CrossRef][Medline]

Lewis, S. E. (2005). Gene Ontology: looking backwards and forwards. Genome Biol 6, 103.[CrossRef][Medline]

Liu, Y., Burch-Smith, T., Schiff, M., Feng, S. & Dinesh-Kumar, S. P. (2004). Molecular chaperone Hsp90 associates with resistance protein N and its signaling proteins SGT1 and Rar1 to modulate an innate immune response in plants. J Biol Chem 279, 2101–2108.[Abstract/Free Full Text]

Lu, R., Malcuit, I., Moffett, P. & 7 other authors (2003). High throughput virus-induced gene silencing implicates heat shock protein 90 in plant disease resistance. EMBO J 22, 5690–5699.[Abstract/Free Full Text]

Maniatis, T., Fritsch, E. F. & Sambrook, J. (1982). Molecular Cloning: a Laboratory Manual. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory.

Marathe, R., Guan, Z., Anandalakshmi, R., Zhao, H. & Dinesh-Kumar, S. (2004). Study of Arabidopsis thaliana resistome in response to cucumber mosaic virus infection using whole genome microarray. Plant Mol Biol 55, 501–520.[CrossRef][Medline]

Martin, D., Brun, C., Remy, E., Mouren, P., Thieffry, D. & Jacq, B. (2004). GOToolBox: functional analysis of gene datasets based on gene ontology. Genome Biol 5, R101.[CrossRef][Medline]

Martins, C. R. F., Johnson, J. A., Lawrence, D. M. & 8 other authors (1998). Sonchus yellow net rhabdovirus nuclear viroplasms contain polymerase-associated proteins. J Virol 72, 5669–5679.[Abstract/Free Full Text]

Maule, A., Leh, V. & Lederer, C. (2002). The dialogue between viruses and hosts in compatible interactions. Curr Opin Plant Biol 5, 279–284.[CrossRef][Medline]

Qanungo, K. R., Shaji, D., Mathur, M. & Banerjee, A. K. (2004). Two RNA polymerase complexes from vesicular stomatitis virus-infected cells that carry out transcription and replication of genome RNA. Proc Natl Acad Sci U S A 101, 5952–5957.[Abstract/Free Full Text]

Ronning, C. M., Stegalkina, S. S., Ascenzi, R. A. & 24 other authors (2003). Comparative analyses of potato expressed sequence tag libraries. Plant Physiol 131, 419–429.[Abstract/Free Full Text]

van Poelwijk, F., Kolkman, J. & Goldbach, R. (1996). Sequence analysis of the 5' ends of tomato spotted wilt virus N mRNAs. Arch Virol 141, 177–184.[CrossRef][Medline]

Weck, P. K. & Wagner, R. R. (1978). Inhibition of RNA synthesis in mouse myeloma cells infected with vesicular stomatitis virus. J Virol 25, 770–780.[Medline]

Whitham, S. A., Quan, S., Chang, H.-S., Cooper, B., Estes, B., Zhu, T., Wang, X. & Hou, Y.-M. (2003). Diverse RNA viruses elicit the expression of common sets of genes in susceptible Arabidopsis thaliana plants. Plant J 33, 271–283.[CrossRef][Medline]

Zhirnov, O. P., Konakova, T. E., Garten, W. & Klenk, H.-D. (1999). Caspase-dependent N-terminal cleavage of influenza virus nucleocapsid protein in infected cells. J Virol 73, 10158–10163.[Abstract/Free Full Text]

Zhong, G. V. & Burns, J. K. (2003). Profiling ethylene-regulated gene expression in Arabidopsis thaliana by microarray analysis. Plant Mol Biol 53, 117–131.[CrossRef][Medline]

Received 17 March 2005; accepted 26 May 2005.



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