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Journal of Virology, March 2008, p. 2324-2329, Vol. 82, No. 5
0022-538X/08/$08.00+0     doi:10.1128/JVI.01930-07
Copyright © 2008, American Society for Microbiology. All Rights Reserved.

Global Transcriptional Responses of Pseudomonas aeruginosa to Phage PRR1 Infection

Janne J. Ravantti, Tanja M. Ruokoranta,^, A. Marika Alapuranen, and Dennis H. Bamford^*

Department of Biological and Environmental Sciences and Institute of Biotechnology, Viikki Biocenter, P.O. Box 56, 00014 University of Helsinki, Finland

Received 4 September 2007/ Accepted 3 December 2007

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The infectious cycles of viruses are known to cause dramatic changes to host cell function. The development of microarray technology has provided means to monitor host cell responses to viral infection at the level of global changes in mRNA levels. We have applied this methodology to investigate gene expression changes caused by a small, icosahedral, single-stranded-RNA phage, PRR1 (a member of the Leviviridae family), on its host, Pseudomonas aeruginosa, at different times during its growth cycle. Viral infection in this system resulted in changes in expression levels of <4% of P. aeruginosa genes. Interestingly, the number of genes affected by viral infection was significantly lower than the number of genes affected by changes in growth conditions during the experiment. Compared with a similar study that focused on the complex, double-stranded-DNA bacterial virus PRD1, it was evident that there were no universal responses to viral infection. However, in both cases, translation was affected in infected cells.

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Over the past few years, microarray technology has been employed to probe the global effects of viral infection on host gene expression (26, 27). The earliest microarray-based studies of host gene expression provided a very general, genome-wide picture of changes induced by viral infection. These studies, however, provided little information about the specific changes in individual genes across the entire host genome. Furthermore, investigations using this technology have largely focused on viral infections in animals and, to a lesser extent, in plants (21, 30, 35) or fungi (2, 3). Microarrays have been employed to detect phage-specific transcripts in infected cells (11, 19), changes in the host genome (14, 20), and changes in the transcriptional profiles of bacteria parasitized by lysogenic phages (7). However, to our knowledge, only two studies of virus-induced changes in host gene expression span the entire host genome. One of these studies involved a plant virus (21), and the other focused on an icosahedral, membrane-containing, double-stranded-DNA (dsDNA) phage, PRD1 (27).

PRR1 is an icosahedral, single-stranded-RNA (ssRNA) phage (24) that is related to well-studied members (MS2, Qbeta, etc.) of the Leviviridae family (13). PRR1 is unique among members of the Leviviridae family in that it infects a wide range of gram-negative bacteria (8, 24), but only if they harbor an IncP-type conjugative plasmid. The PRR1 genome contains 3,573 nucleotides with only four protein-encoding genes, namely, those for the polymerase, the maturation and coat proteins, and the lytic factor (28). The PRR1 replication cycle and its effects on host cell physiology are described elsewhere (G. Daujotaitë, R. Daugelavièius, and D. H. Bamford, submitted for publication). The optimal bacterial host for PRR1 is Pseudomonas aeruginosa (24), a gram-negative, opportunistic human pathogen (15, 16, 18). At 6.3 million base pairs (containing 5,570 open reading frames [ORFs]), the P. aeruginosa genome is one of the largest bacterial genomes that has been sequenced (31). More than 9% of the known ORFs are classified as transcriptional regulators or two-component systems, reflecting the importance of transcriptional regulation in the ability of P. aeruginosa to respond and adapt to a myriad of environments (31). Interestingly, over 300 quorum-sensing control genes (6% of the P. aeruginosa genome) have also been identified (29, 34). In this study, P. aeruginosa O1 (PAO1) DNA microarrays were utilized to identify genes whose expression levels were affected by infection with PRR1. When we monitored gene expression changes at various time points after infection, we found that viral infection did not grossly affect cell metabolism until the time of lysis. The genes most affected by PRR1 infection were grouped into three major functional classes, namely, transport, energy production, and protein synthesis. To determine whether these changes in gene expression are a general effect of phage infection or are specific to infection by PRR1, the data set was compared with a similar study of PRD1, a well-characterized icosahedral dsDNA model virus that utilizes the same cell surface receptor complex as PRR1 (1, 4, 9, 22, 23, 25).

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Sample collection. PRR1 was propagated in the P. aeruginosa O1 (PAO1) (17) strain carrying an IncP plasmid (25). Cells were grown at 37°C in MOPS (morpholinepropanesulfonic acid)-buffered Luria-Bertani broth at pH 7.4. The overnight culture was diluted in fresh medium (from 1.5 to 50 ml) and grown aerobically at 37°C for 2.0 h (to an A₆₀₀ of 1.5). A second, 12-fold dilution was performed to reach an optical density (A₆₀₀) of 0.10 to 0.13. At this point, the culture was divided into two parts. Aeration was continued at 37°C until the A₆₀₀ reached a value of 1.0. One portion of the culture was infected with phage PRR1 at a multiplicity of infection of 10. The other portion was used as an uninfected control culture. Both cultures were aerated continuously at 37°C.

Samples for RNA isolation were taken from both the infected and uninfected cultures at time points corresponding to 5, 10, 15, 30, and 50 min postinfection (p.i.). Additional samples were collected from the control culture at the time of infection (i.e., the 0-min sample). At each time point, two different samples were collected, one for RNA isolation and one for viable cell counts and A₆₀₀ measurements. All samples were processed immediately. Three independent replicates of the experiment were performed.

Isolation of total RNA. Total RNA was isolated from 1.9 x 10¹⁰ cells (10 ml of the cell culture) with two phenol and three ether extractions. In the first extraction, the phenol (pH 4.3; Sigma) was preheated to 95 to 100°C and the sample was supplemented with 1 ml lysis buffer (0.5 M Tris-HCl, pH 7.5, 0.2 M EDTA, and 10% sodium dodecyl sulfate) to ensure rapid cell lysis. The nucleic acids were precipitated from the aqueous phase with sodium acetate and ethanol. Further purification was performed using an RNeasy Midi kit (Qiagen) and on-column DNase (Qiagen) digestion according to the manufacturer's instructions. The purified RNA samples were stored at –80°C. The concentration and purity of the RNA samples were determined by measuring the A₂₆₀/A₂₈₀ ratio. These readings were in the range of 2.0 to 2.2 for all samples. The integrity of the total RNA was confirmed by denaturing electrophoresis on formaldehyde-agarose gels, followed by staining with ethidium bromide.

Microarray data analysis. cDNA synthesis, labeling, hybridizations, and data collection were performed by CTL Bio Services (Rockville, MD) according to standard Affymetrix GeneChip procedures. Labeled cDNA was used to probe an Affymetrix GeneChip comprised of 5,900 spots that represented 5,769 probes for the PAO1 genome, including 5,570 predicted ORFs and rRNA and tRNA genes, as well as 199 probe sets corresponding to 100 intergenic regions. In addition, 14 probes served as controls, including genes from Bacillus subtilis, Arabidopsis thaliana, and Saccharomyces cerevisiae. The raw data and the annotated PAO1 genome were imported into GeneSpring GX software, version 7.3 (Agilent Technologies). GeneSpring GX was used to normalize the data prior to further processing. Several custom-made scripts were used to calculate the changes in gene expression levels within experimental replicates and between the infected samples and the control (uninfected) samples. Expression level changes were considered significant if they differed at least twofold and had a Student's t test P value of <0.05. We chose gene selection criteria that were lenient compared with those of our previous array experiments (27) because PAO1 displayed low variability in gene expression levels compared with cells infected with PRD1.

Microarray validation and qRT-PCR. Differential expression of selected genes was examined by quantitative real-time reverse transcription-PCR (qRT-PCR). In each case, qRT-PCR was performed on the same three biological replicates that were used for the microarray experiments. In addition, one to three technical replicates were carried out for each sample. RNA samples were treated with DNase (RQ1 DNase; Promega) and purified with an RNeasy MinElute cleanup kit (Qiagen). cDNA was generated using random hexamers and Moloney murine leukemia virus reverse transcriptase (Finnzymes). qRT-PCR was performed using a Dynamo SYBR green 2-step qRT-PCR kit (Finnzymes) according to the manufacturer's instructions. Primers were designed with the assistance of PrimerExpress software (Applied Biosystems). The following primer sequences were used: for PA4407 (ftsZ), 5'-CGAGCAGCAGTCGGTGAACTAC-3' (forward) and 5'-GTGAGACTGGTTGCGCATCA-3' (reverse); for PA3126 (ibpA), 5'-TCGGCCCTGCGTAATGAG-3' (forward) and 5'-GATACTCGTCGTCACCGTGCT-3' (reverse); for PA3183 (zwf), 5'-GAGCCGCCGCACTACATC-3' (forward) and 5'-TGGTCCTTGGTCATCACTTGC-3' (reverse); for PA0447 (gcdH), 5'-CGGCATCTCCGACGAATTC-3' (forward) and 5'-GTGCCCTCGTAGGTGTTCACC-3' (reverse); and for PA4268 (rpsL), 5'-CCAACGGTTTCGAGGTTTCC-3' (forward) and 5'-CGCTGTGCTCTTGCAGGTT-3' (reverse). All samples were normalized to the cell division gene ftsZ to control for the amount of cDNA in each reaction mix. Measurements were obtained using an ABI 7000 sequence detection system (Applied Biosystems) and a program of 15 min at 95°C and 40 cycles of 10 s at 94°C, 30 s at 60°C, and 30 s at 72°C. qPCR product dissociation curves were used to verify the specificity of the amplified product. Melting curves for PCR specificity analysis were obtained following the completion of the amplification reactions, using the following conditions: 15 s at 95°C, 20 s at 60°C, and 15 s at 95°C. Raw data were analyzed using ABI Prism 7000 software (Applied Biosystems), and relative quantification was performed using Microsoft Excel. The 0-min samples were used as calibration samples for the cycle threshold method (relative quantifications).

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Dissection of virus-induced changes. To distinguish virus-induced changes from changes associated with normal host growth, we constructed two experimental protocols (Fig. 1). The control experimental protocol was designed to monitor gene expression in uninfected bacterial culture over the entire time frame of infection (expression in uninfected sample at time x = E_x, normalized to expression in the uninfected sample at time zero [E₀], i.e., E_x/E₀, where x = 5, 10, 15, 30, and 50 min). The second protocol allowed us to evaluate the differences between the infected and uninfected cultures for each experimental time point (expression in infected sample at time x = P_x, normalized to expression in the uninfected sample at time x [E_x], i.e., P_x/E_x, where x = 5, 10, 15, 30, and 50 min). Combining these two measurements established the mRNA content of a given gene in the infected cell compared to its abundance prior to infection (expression in the infected sample at time x, normalized to expression in the uninfected sample at time zero, i.e., E_x/E₀ x P_x/E_x = P_x/E₀).

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FIG. 1. Experimental protocol. P. aeruginosa O1 cells were cultured in Luria-Bertani broth, with aeration, to exponential growth phase. The cultures were divided into two parts, and one of the subcultures was infected with phage PRR1 (multiplicity of infection of 10). Turbidity values (OD600) from three independent experiments, plotted as a function of time (dashed lines, infected cells; solid lines, uninfected cells), are depicted. The time point for virus addition is indicated by an arrow. Samples were collected for total RNA isolation at six time points (0, 5, 10, 15, 30, and 50 min p.i. [black circles]) and at equivalent time points for uninfected cultures.

Verification of microarray data by qPCR analysis. To determine the reliability of the genome-wide microarray data, we selected individual genes and analyzed their expression changes by qPCR. We chose four genes, namely, PA0447 (gcdH), PA3126 (ibpA), PA3183 (zwf), and PA4268 (rpsL), which represented a range of expression level changes (Fig. 2). In each instance, the results of the qPCR analysis were in close agreement with those obtained from the genome-wide, microarray-based analysis, indicating that the microarray-based data set is sufficiently robust to monitor the expression of individual genes.

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FIG. 2. Verification of microarray results by qPCR analysis. Comparisons of mRNA levels were performed with noninfected and PRR1-infected cells by microarray analysis and qPCR for selected P. aeruginosa genes. Genes are indicated at the left side of each panel. Solid lines, uninfected x-min samples versus uninfected 0-min sample (Ex/E0); dashed lines, infected x-min samples versus uninfected 0-min sample (Px/E0).

Global growth phase-dependent gene expression changes in uninfected P. aeruginosa cells. The physiological state and transcriptional activity of the uninfected cells were not constant during the required time frame for PRR1 production (Daujotaitë et al., submitted). Even in the uninfected culture, the growth rate began to decline at the 60-min p.i. time point (Fig. 1), indicating that the bacteria were facing nutrient exhaustion and were preparing for stationary phase. Using stringent criteria for the identification of genes that showed expression changes (see note in Table 1), we found that 263 of the 5,549 PAO1 genes had significant changes in expression level by the time the cells had reached the 50-min p.i. time point. The alterations in gene expression became more pronounced as the cells reached late logarithmic phase and approached stationary phase. In general, up-regulation of genes was much more common than down-regulation throughout the 50-min time interval (Table 1). The complete list of genes that displayed changes in expression level can be found in supplemental material online (http://blogit.helsinki.fi/bamford/supplements.htm). Interestingly, a notable portion of the down-regulated genes were involved in translation (e.g., ribosomal proteins). These changes are likely to reflect cellular metabolic changes in response to the decreasing nutrient availability in the medium.

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TABLE 1. Global changes in PAO1 gene expression during PRR1 infectiona

Global virus-induced changes in host gene expression. We monitored the growth rates of infected PAO1 cultures in parallel with their gene expression changes. We observed that in the first 30 min following infection, there were no detectable changes in cellular growth rate compared with uninfected control cells (Fig. 1). However, between 30 and 60 min p.i., the culture turbidity remained relatively constant, indicating that growth arrest had occurred. This was followed by a decrease in culture turbidity, consistent with cell lysis. These virus-induced effects on PAO1 growth are very similar to physiological changes that have been observed previously (Daujotaitë et al., submitted). Surprisingly, the PRR1-induced changes in host gene expression were relatively small, and the total number of genes that showed altered expression was only 190 (Table 1). Under these conditions, the vast majority of genes with altered expression levels were down-regulated, in contrast to the growth phase-dependent changes (see above).

PRR1-infected cultures have been shown to produce up to 1,000 infectious particles per cell. They also produce semicrystalline, intracellular aggregates, estimated to contain as many as 4,000 viral particles (Daujotaitë et al., submitted). It is also possible that a fraction of the viral particles produced are noninfectious. Thus, the total number of viral particles produced by each cell may be considerably larger than the estimated number of infectious particles produced. However, owing to the small mass (4 MDa) of members of the Leviviridae family, the fraction of cellular synthesis of macromolecules directed to virus production is likely still very small. For example, in the case of PRD1 (66 MDa), approximately 200 particles are produced per cell. Since the mass ratio between PRD1 and PRR1 is approximately 18, the approximately 4,000 PRR1 particles per cell would be roughly equal in terms of viral mass to the mass produced by a PRD1-infected cell. This total viral mass corresponds to only about 10% of the total cellular macromolecule pool (27). Consequently, PRR1, like PRD1, appears to replicate in the cell with little interference to the host cell life cycle until late in infection (30 min p.i.). This view differs from a previous model that proposed that the entire synthesis capacity and cellular macromolecule pool are harnessed for virus production (12). However, our observation that both cell growth and host gene expression are virtually unchanged during the first 30 min p.i. is consistent with the notion that PRR1, as well as PRD1 (27), has minimal effects on the host cell. In fact, even as cells succumb to PRR1-directed lysis, the number of genes that show expression level changes is fewer than the number of genes that change as cells prepare to enter stationary phase. Thus, for most of the PRR1 infectious cycle, its effects on host cell physiology appear to be very small.

Gene-specific changes due to cellular growth and viral infection. We next compiled a list of genes that showed the greatest expression level changes and compared their annotated functions. This analysis revealed that the genes most dramatically affected by PRR1 infection tend to be involved in one of three major cellular functions, i.e., transport, energy production, and protein synthesis (Table 2). Genes involved in these processes represent 69 of the 190 genes whose expression levels changed in response to PRR1 infection. Further analysis of the microarray data set revealed that in almost all cases, several genes in a single operon were coregulated. Notably, PRR1 infection caused the up-regulation of the heat shock protein gene ibpA beginning at 30 min p.i. Late in the infection, the clpC (encoding the ATP-binding subunit of an ATPase with chaperone activity), rpo, and yhb (both involved in transcription) genes were all down-regulated. In contrast, at equivalent time points in uninfected control cells, these three genes were all up-regulated (Table 2, "Others"). When the uninfected cells reached late logarithmic growth phase (at 50 min p.i.), the expression of genes encoding basic metabolic pathways (e.g., glycolysis, tricarboxylic acid cycle, Enter-Doudoroff pathway) was down-regulated. However, only minor changes to this pattern were observed in infected cells at an equivalent time point. The general trend was that such pathways were further down-regulated.

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TABLE 2. Regulation of selected gene groupsa

(i) Transport/export. During PAO1 growth, we observed a consistent up-regulation of genes involved in small-molecule transport at 50 min p.i. (27 genes residing in eight operons; note that the glt operon is an exception). This apparently reflects the physiological changes taking place when nutrients in the batch culture growth medium diminish and more effective uptake is needed. In infected cells, however, there was a reversal of this regulation toward the end of the virus life cycle. During this time period (30 to 50 min p.i.), the turbidity of the infected culture did not increase and there may not have been a need for additional nutrient uptake. Alternatively, activation of the lysis system by PRR1, which results in inhibition of peptidoglycan synthesis (6, 36), may interfere with the integrity of the cell envelope (Daujotaitë et al., submitted). The loss of cell envelope integrity may compromise the cell's ability to up-regulate transport-related genes.

(ii) Energy production/conversion. Expression of the ccoO (cytochrome oxidase) gene was down-regulated late in infection but was up-regulated in uninfected control cells. The nir and pse genes were regulated similarly in both infected and uninfected cells. The most prominent effect of PRR1 infection was found among the nar genes, which were up-regulated.

(iii) Ribosomal proteins. As a whole, PRR1 infection had the most significant effect on the genes that encode ribosomal proteins. Up to 38 genes in this category were affected. In uninfected control cells, several ribosomal protein genes were up-regulated at the 15-min time point, followed by a marked down-regulation at 50 min. Surprisingly, in PRR1-infected cells, this strong down-regulation of ribosomal protein genes occurred at the 15-min time point. A similar pattern of expression was observed for the tsf and tuf genes, which encode translation elongation factors that are used as replication cofactors by the viral polymerase in leviviral infections (33). At this time point, viral replication is complete and coat protein synthesis has just begun (as shown for phage f2 [5, 32]). The increase in culture turbidity terminated at 30 min p.i. (Fig. 1). These observations are consistent with the notion that only a small fraction of the cell's protein synthesis capacity is needed to produce virions late in infection and, therefore, that no boost in ribosome biogenesis is required.

Comparison of PRR1- and PRD1-induced host gene expression changes. PRR1 is a small icosahedral ssRNA virus, whereas PRD1 is a complex, membrane-containing icosahedral dsDNA virus. However, both depend on the same membrane-associated conjugative tra complex for cellular entry and, consequently, share the same broad host range (10). The durations of the viral life cycle in liquid medium are approximately the same for these viruses (cell lysis starts at 50 to 60 min p.i.), and in both cases, similar total virion masses are produced by infected cells. A surprising observation with the PRD1 system was that the virus did not cause significant changes to host cell metabolism (only 8% of genes were found to be down- or up-regulated due to viral infection, compared with 9% of genes which were changed due to physiological changes) (27). In the case of PRR1, an even smaller number of host genes responded to viral infection (4% due to virus infection and 5% due to physiological changes). To determine whether the host responds universally to viral infections, we compared the subset of genes that responded to PRR1 infection to those that responded to PRD1 infection. Overall, we found very little overlap between specific genes that showed expression level changes between these two systems. However, both viruses caused down-regulation of protein synthesis, albeit at different time points (15 min p.i. for PRR1 and 30 min p.i. for PRD1). A large number of heat shock genes were strongly up-regulated during PRD1 infection, whereas in the case of PRR1, only ipbA expression was significantly increased. Thus, this analysis suggests that the down-regulation of protein synthesis may be the only universal response to viral infection and may be required to maintain the energy needed for virus production, since protein synthesis is an energy-expensive process.

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It has generally been considered that viruses commandeer the macromolecular synthesis capacity of the host cell for viral reproduction. In this investigation, we did not observe such a drastic overtake, at least at the level of transcription. We did, however, observe considerable changes in the expression levels of ribosomal proteins, pointing to major effects at the level of translation.

However, we have provided evidence that the PRR1 phage, like PRD1, replicates within bacterial cells with minimal effects on the major biosynthetic pathways of the host, other than protein synthesis. Since no drastic changes were observed, it seems that host cells act merely as passive vessels for virus multiplication. In this respect, PRR1 is even more invisible to the host than PRD1. This analysis also demonstrates that each virus affects the host in unique ways, since the set of genes altered by PRR1 shows little overlap with those altered by PRD1.

 
We acknowledge the technical assistance provided by the Bamford Laboratory personnel.

This work was supported by the Finnish Center of Excellence Program (2006-2011) of the Academy of Finland (grants 1213467 and 1213992 to D.H.B.).

 
* Corresponding author. Mailing address: Viikki Biocenter 2, P.O. Box 56, Viikinkaari 5, FIN-00014 University of Helsinki, Finland. Phone: 358-9-19159100. Fax: 358-9-19159098. E-mail: dennis.bamford{at}helsinki.fi

Published ahead of print on 12 December 2007.

J.J.R. and T.M.R. contributed equally to this work.

Present address: Vactech Oy, Biokatu 8, 33520 Tampere, Finland.

Present address: Roal Oy, P.O. Box 57, 05201 Rajamäki, Finland.

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Journal of Virology, March 2008, p. 2324-2329, Vol. 82, No. 5
0022-538X/08/$08.00+0     doi:10.1128/JVI.01930-07
Copyright © 2008, American Society for Microbiology. All Rights Reserved.

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