1 Glasgow University Department of Neurology, Southern General Hospital, Institute of Neurological Sciences, Glasgow G51 4TF, UK
2 Scottish Centre for Genomic Technology and Informatics, Medical School, University of Edinburgh, Edinburgh EH16 4SB, UK
Correspondence
Peter G. E. Kennedy
P.G.Kennedy{at}clinmed.gla.ac.uk
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ABSTRACT |
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A list of VZV PCR primers is shown in Supplementary Table S1, a summary of RT-PCR results in MeWo and SVG cells in Supplementary Table S2, in situ hybridization using DIG-labelled probes to VZV gene 63 in VZV-infected MeWo and SVG cells at 72 h post-infection in Supplementary Fig. S1, and gels of RT-PCR experiments for VZV genes 31 and 61 in Supplementary Figs S2 and S3, available as supplementary material in JGV Online.
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INTRODUCTION |
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A detailed analysis of viral transcription both in vitro and in vivo is important in terms of understanding the biology of VZV, including viral latency, and in the identification of potential viral targets that can be exploited therapeutically (Cohrs et al., 1994, 1995
, 1996
, 1998
, 2003a
, b
; Kennedy et al., 1998
, 2000
). The development of gene microarray technology in which the entire viral transcriptome can be determined during infection has added a new dimension to such studies. A PCR-based VZV array system using predicted viral open reading frames (ORFs) has recently identified highly expressed viral genes during acute lytic infection (Cohrs et al., 2003b
), and we have previously described the use of long-oligonucleotide arrays in analysing global viral gene transcription during infection by alpha, beta and gamma members of the herpesvirus family (Chambers et al., 1999
; Ebrahimi et al., 2003
; Stingley et al., 2000
; Wagner et al., 2002
). Here we report the construction and validation of a novel VZV oligonucleotide microarray system, and show that it can be used to detect differences in the viral transcriptome in different cell types.
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METHODS |
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Isolation of RNA.
RNA was extracted from cells using Qiagen RNeasy kits. Approximately 107 cells were trypsinized from the flasks and resuspended in lysis buffer containing -mercaptoethanol. The samples were placed on a QIAshredder spin column and centrifuged at maximum speed for 2 min. An equal volume of 70 % ethanol was added to the flow-through which was placed on the Qiagen column, washed and then DNase (Qiagen RNase-free DNase) was added to the column. After several washes, the RNA was eluted and it was usually necessary to DNase-treat again (DNA-free kit, Ambion). The absence of residual DNA was shown by PCR for
-actin. RT-PCR was performed on all samples, and as a further check for DNA contamination, PCR was also performed on samples which were not reverse transcribed. RT-PCR also provided a validation for the presence of VZV-specific RNAs. Primers for VZV genes 37 (late, L), 28 (early, E) and 63 (immediate early, IE), as well as 62 (IE), 10 (L), 31 (L) and 4 (IE) were used, as well as nested primers for genes 63 and 62 (refer to Supplementary Table S1 for all VZV PCR primers used in this study). All of these VZV genes could be detected by RT-PCR (gels of RT-PCR experiments for VZV genes 31 and 61 are shown in Supplementary Figs S2 and S3).
The total RNA samples were quality-control checked on 2100 Bioanalyser NanoChips (Agilent) and a BioMate 5 UV spectrophotometer (Thermo Spectronic).
Array hybridization.
Biotin [-dUTP (50 nmol), Roche Diagnostics] -labelled cDNA was synthesized from 2·5 µg total RNA, as specified by the manufacturer (Protocol for Direct Labelling for cDNA with Biotin-dUTP, Qiagen). The biotinylated target cDNAs were hybridized to the arrays (18 h at 42 °C), washed, HiLight Resonance Light Gold Particle hybridized (1 h at room temperature) and washed, as specified by the manufacturer (HiLight Array Detection Protocols For Single-Colour Detection on the HiLight Reader using Resonance Light Scattering, Qiagen).
Data processing and statistical analysis.
Array hybridization and analysis followed standard operating procedures, as described by Forster et al. (2003). Array data can be accessed at the MIAME-compliant database GPX, accession no. GXE-00039 (http://www.gti.ed.ac.uk/GPX/).
Image quantification.
QUANTARRAY (Packard Biosciences) image analysis software (with histogram quantification correction) was used for initial data capture. A typical hybridization image is shown in Fig. 1. To define the linear dynamic range of the biotingold particle light scatter and to control for scanning parameters (exposure time of the white-light source), arrays were scanned at five increasing exposure times, thereby initially generating five datasets per array. These datasets were then analysed against each other by scatter plots. The scan with the highest linear range of expression but no genes saturated at the 16-bit scan limits (maximum intensity value=65535) was chosen as the dataset best representing an array.
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Print quality correction.
Triplicate printing of each probe on an array allowed us to compute the median expression value of each such triplicate as the representative value for this gene.
Array quality control.
Receiver-operating-characteristics (ROC) analysis was performed for each array hybridization in the study. Sets of known positive- (n=30) and negative-control probes (n=156, including unused spike controls) on the chip represented the gold standard, against which the expression values were compared. The area under curve (AUC) was calculated for each array. Clear distinction (AUC close to 1) of positive and negative controls was taken to be an indicator of array/hybridization quality, since a high value meant that the expression values for known positive- and negative-control probes did not overlap. An AUC close to 0·5 would indicate that there is no expression-level cut-off that can clearly distinguish between positive and negative signals. As a consequence, one biological replicate from the non-infected MeWo cell line was withdrawn from analysis.
Data transformation.
Following the above, for further processing, the log2 of all data was obtained.
Normalization.
The chosen method was scaling of the array medians to a common reference value by adding a correctional constant (Forster et al., 2003). Normalization estimates were based on a set of host-encoded housekeeping genes (n=30), because a global normalization method based on the distribution of all probes on the array is inappropriate for most targeted (i.e. genome subset) arrays. For a targeted array, it can be assumed that a large proportion of genes will change expression between uninfected and infected samples; any overall expression differences between different samples are therefore due to hybridization/scanning and to real biological differences. All 30 housekeeping spots were assessed for consistency by means of a k-means clustering on their raw expression values across all arrays. As a result of this, the most reliable and rank-invariant set was chosen as the normalization set (n=12) accounting for hybridization/scanning effects only. These are triplicate spots of probes representing major histocompatibility complex 1 (MHC1),
-tubulin, glyceraldehyde-3-phosphate deydrogenase (GAPDH) and myosin light chain (alkali) Alt. Splice2.
Measurement thresholding.
Subsequent to normalization, the lower threshold for reliable measurement of gene-expression values was computed as the 80th percentile of signal intensities of the Arabidopsis thaliana negative controls (n=18x3). This threshold level was used to determine whether a signal was above the detection error associated with each individual array. The threshold level value was subtracted from the expression value for each ORF. In tables and figures, a value lower than 0 is represented as a 1.
Inference analysis.
Statistical comparisons were performed for each gene to determine the significance of differential expression between infected and uninfected samples. The statistical sample size was n=5 independent biological samples per group, except for the MeWo non-infected group, for which n=4 (see Methods). Although sufficient for the computation of test statistics, a per-condition sample size of five limited the direct biological interpretability of results without laboratory validation. However, this study did include RT-PCR measurements as a means of validating the microarray results. Interpretation of results was done on the premise that the significance tests serve as a valid interest filter. To make optimum use of the microarray platform and the given sample sizes, the method of analysis was a permutation of Welch's t test performed on log2-transformed data. A Westfall and Young step-down adjustment was used on the resulting P values to correct for problems created by testing multiple genes simultaneously.
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RESULTS AND DISUSSION |
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The array design used probes with a high degree of biophysical and thermodynamic equivalence, and allowed the determination of both the stringency and polarity of viral gene expression. The latter was also quantified using robust statistical analyses. A comparison of our results with the recent study of Cohrs et al. (2003b) reveals that the transcription of some viral genes was significantly elevated in both systems. Thus, there was a striking detection of the transcription of VZV ORF 9 in MeWo cells infected with VZV, this gene being consistently highly transcribed in lytically infected cultures. This is the first independent confirmation of the finding of Cohrs et al. (2003b)
that ORF 9 is the most highly expressed ORF in BSC-1 cells infected with the VZV Ellen laboratory strain. This protein is known to be an abundant tegument phosphoprotein, the protein being phosphorylated by the ORF 47-encoded protein kinase (Ng & Grose, 1992
; Ng et al., 1994
), and then associating with phosphorylated IE 62 protein (Spengler et al., 2001
). The oligonucleotide probes selected provide a global and simultaneous readout of VZV ORF transcriptional activity. In addition, transcriptional polarity is defined, since the probes are single stranded and of sense orientation. However, the probes were not designed to address the fine details of VZV transcriptional complexity. Indeed, a limitation of this approach is that the array probes do not allow for the differentiation of co-terminal and collinear transcripts, which is a feature of VZV transcription. In this respect, certain probes (e.g. for ORFs 4/5 and 63/64) probably detect multiple transcripts arising from the same strand.
The six most abundant VZV transcripts detected in MeWo cells infected by the laboratory-adapted Dumas VZV strain were ORFs 57, then 9, 49, 58, 48 and 69. Four of these ORFs were also in the top six transcribed genes in the study of Cohrs et al. (2003b), namely ORFs 9, 49, 57 and 69 (ORF 64 was highly expressed in the previous study, and ORFs 64 and 69 are duplicated genes). The HSV 1 homologue of the protein encoded by ORF 49 has been identified as a virion protein (MacLean et al., 1989
), while the protein encoded by ORF 57 is a hypothetical protein, which has yet to be identified but is dispensable for virus replication in cell culture (Cox et al., 1998
). ORF 33, which encodes a protease (McMillan et al., 1997
), was not significantly expressed in MeWo cells, despite being highly expressed in BSC-1 cells infected with VZV Ellen (Cohrs et al., 2003b
). ORF 64/69 encodes a 19·8 kDa protein which is dispensable for virus replication (Sommer et al., 2001
). Despite the not-unexpected differences, these transcriptional similarities between the two systems reinforce the reliability of microarray technology.
Both the cell type used for infection (MeWo versus BSC-1) and the strain of virus used (Dumas versus Ellen) were different in the Cohrs et al. (2003b) study and this study, and this is presumably a major contributing reason for the differences observed. In our study, the transcriptome of VZV Dumas strain on either the MeWo cells (known to be VZV-permissive) or SVG cells was analysed at 72 h and found to differ markedly, as shown in Table 5
. Since the same virus was used in both cases, and the ratio between the top 20 % of viral and invariant cellular genes was equivalent, we conclude that the infected host-cell type influences the viral transcriptome. It is known that during acute VZV infection of cultured human astroglial cells, host-protein synthesis may be altered, as evidenced by the down-regulation of glial fibrillary acidic protein (GFAP) under these conditions (Kennedy et al., 1994
). Since SVG cells are also astroglial, it is possible that some form of host-cell modulation by the infection may have affected the virushost cell interaction to produce the observed phenotype.
To date we, and others, have performed a large number of diverse microarray studies of herpesvirus family genomes, including the analysis of a wide range of different strains and mutant genomes (Chambers et al., 1999; Ebrahimi et al., 2003
; Jenner et al., 2001
; Stingley et al., 2000
; Sun et al., 2004
; Wagner et al., 2002
; Yang et al., 2002
). Overall, these experiments reveal a marked robustness of the herpes viral transcription programme. A key property of robust systems is their general insensitivity to changes of internal parameters. We also have preliminary data (P. G. E. Kennedy and others, unpublished results), based on two different VZV patient isolates, that suggest that the viral RNA transcriptional signatures may differ markedly from patient to patient, but much further work will be required to determine whether this can be used as a potential correlate or predictor of the development of PHN. Both oligonucleotide- and PCR-based VZV arrays are very likely to prove powerful tools for the future investigation of viral gene function, and may also have diagnostic potential.
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ACKNOWLEDGEMENTS |
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Received 4 February 2005;
accepted 23 June 2005.