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Previous Article | Next Article 
Journal of Bacteriology, December 2003, p. 7222-7230, Vol. 185, No. 24
0021-9193/03/$08.00+0 DOI: 10.1128/JB.185.24.7222-7230.2003
Copyright © 2003, American
Society for
Microbiology. All Rights Reserved.
INSERM EMI 9933, Epidémiologie de la Résistance aux Anti-infectieux, and AP-HP Groupe Hospitalier Bichat-Claude Bernard, 75877 Paris Cedex 18, France,1 Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 021152
Received 1 September 2003/ Accepted 29 September 2003
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ABSTRACT |
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INTRODUCTION |
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The transcription of genes encoding several virulence factors of P. aeruginosa is controlled by the two quorum-sensing (QS) systems, las and rhl (19), which are regulated by autoinducers (30). Our knowledge of these two QS systems in P. aeruginosa has rapidly progressed in the last decade (for a recent review, see reference 4). The las system controls the expression of virulence genes such as lasA, lasB, aprA, toxA, and lasI (6, 7, 17, 23, 28). The rhl system controls, for example, the expression of lasA, lasB, and rhlAB (2, 3, 11, 12, 15, 18, 30). The las and rhl QS systems are hierarchically linked. The las system positively regulates the expression of both rhlR and rhlI (11, 19).
In vitro studies with primarily laboratory strains and virulence studies in animals with these same strains have suggested a role for QS systems in pathogenesis. However, the importance of QS in clinical isolates from typical human P. aeruginosa infections is not clearly known (21). A recent study (25) showed a positive correlation between the accumulation of lasR transcripts and those of lasA, lasB, and toxA in sputum samples from cystic fibrosis (CF) patients infected with P. aeruginosa, suggesting that the las system controls virulence gene expression during the course of this specific infection. The autoinducers have also been detected in sputum from patients with CF that also had high levels of lasI and lasR transcripts (5, 24, 25). However, detection of the autoinducers and lasI and lasR transcripts remained low for several CF patients infected by P. aeruginosa (5, 25), and due to the high immune responses of CF patients to virulence factors, it is unclear in this setting of chronic infection whether QS-controlled proteins remain effective virulence factors. As there has been little investigation into the role of QS in P. aeruginosa strains outside of CF, it may be that some isolates do not possess or do not express the QS systems yet remain capable of causing serious human infections.
In order to determine the presence and function of the QS gene lasR among non-CF clinical isolates, we analyzed the sequence of most of the lasR gene from a collection of 66 P. aeruginosa strains isolated from cases of nosocomial pneumonia in ventilated patients hospitalized in an intensive care unit, from cases of bacteremia in cancer patients with neutropenia, and from water from swimming pools and rivers (20). A subset of these strains selected on the basis of genetic diversity of the lasR gene sequence and of the origin of strains was further used to quantify the amount of mRNA transcribed by lasR, lasB, and aprA genes during the growth of these strains by using real-time reverse transcription-PCR.
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MATERIALS AND METHODS |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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DNA extraction, amplification, and sequencing of lasR, lasB, and aprA. DNA extraction was performed by using MagnaPure LC (Roche, Mannheim, Germany) according to the manufacturer's recommendations with slight modifications. Bacteria from the frozen stocks were inoculated onto Mueller-Hinton agar (Sanofi-Pasteur, Marnes-la-coquette, France). After overnight growth at 37°C, one colony was suspended in 60 µl of DNase-RNase-free water (Sigma-Aldrich, Saint Quentin Fallavier, France) with 2 µl of lysozyme at 20 mg/ml (Sigma-Aldrich) and incubated for 5 min at 37°C. One hundred thirty microliters of bacterial lysis buffer supplied in isolation kit III (Roche) was added to the mixture, and the mixture was incubated for 10 min at 65°C. Twenty microliters of proteinase K was also added to the mixture. After the mixture was incubated for 10 min at 95°C, DNA was extracted by using the MagNA Pure LC and the other products of kit III (Roche). DNA was quantified at an optical density of 260 nm with a Gene Quant II spectrophotometer (Amersham-Pharmacia Biotech, Orsay, France).
Internal fragments of 665 bp of the lasR gene, 441 bp of the lasB gene, and 728 bp of the aprA gene were amplified in an I-cycler (Bio-Rad, Marnes-la-coquette, France). An internal fragment of the lasR gene from each of the 66 strains was amplified and sequenced by using primers that encompassed the 5' and 3' ends of the gene to ensure that most of the gene from each strain would be amplified. We did not use primers outside of the coding sequence for lasR because the variability of the nucleotide sequence around the lasR gene was unknown. The nucleotide sequence recovered 92.4% of the lasR gene, which was a good reflection of the overall variation in the lasR gene; the remaining 7.6% of the lasR sequence was from the primers used for PCR amplification. Internal fragments of lasB and aprA genes from the 35 strains selected for real-time PCR were amplified and sequenced in order to choose pairs of primers for amplification and fluorogenic probes that encompassed the region of the genes with the fewest nucleotide changes among all 35 strains. The primers used for amplification are listed in Table 1.
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The PCR products were purified by using the PCR purification kit Qiaquick (Qiagen, Courtaboeuf, France) and then quantified following electrophoresis on agarose gels by using visual comparisons with markers of known quantity (Low DNA Mass Ladder; Boehringer GmbH). The PCR products were sequenced according to the manufacturer's recommendations for the ABI Prism sequencing kit (Applera) by using the same two primers that were used in amplification (Table 1). The non-primer-derived sequences were aligned and compared to those of the published PAO1 strain by using the Sequence Navigator program (Applera).
RNA extraction and purification. RNA was extracted from 35 of the strains, which were chosen based on their origin and their lasR gene sequences, which are representative of each category of clinical isolate, and from PAO1 and its mutant in the lasR gene, PAOR. The 35 strains included the following: (i) 11 strains with lasR gene sequences identical to that of PAO1 and 11 strains with silent lasR mutations, both groups having a similar distribution in terms of clinical source and comprising 4 strains isolated from patients with pneumonia, 4 strains from patients with bacteremia, and 3 strains from environmental water isolates; (ii) 10 strains with mutations in the lasR gene compared with the PAO1 lasR sequence and with a similar distribution in regard to clinical source; and (iii) three strains with an inserted sequence in lasR.
One colony of each strain was inoculated into 5 ml of Luria-Bertani broth and grown overnight at 37°C with shaking. Five hundred microliters of this overnight culture was inoculated into 200 ml of fresh broth and incubated under the same growth conditions. For PAOR cultures, 300 µg of carbenicillin (Sigma-Aldrich, Saint Quentin Fallavier, France) per ml was added. After 120 min of growth, the optical density of the culture at 600 nm was measured with a Spectronic 301 spectrophotometer (Bioblock Scientific, Paris, France). After 120 and 300 min of growth, a volume of culture corresponding to 2 x 108 bacteria was centrifuged for 5 min at 6,000 x g at 4°C. The bacterial pellet was immediately suspended in 100 µl of Tris-EDTA lysis buffer (10 mM Tris-Cl, 1 mM EDTA, pH 8.0) containing 400 µg of lysozyme (Sigma-Aldrich) per ml and incubated for 3 min at room temperature. Three hundred fifty microliters of RLT buffer (Qiagen) containing 0.145 µM ß-mercaptoethanol was added, and the mixture was vigorously shaken, immediately frozen in liquid nitrogen, and stored at -80°C until RNA extraction.
The bacterial lysates were defrosted and centrifuged for 2 min at 6,000 x g at 4°C. Supernatant samples of 450 µl were transferred to microcentrifuge tubes, and 250 µl of absolute ethanol was added to each tube to precipitate nucleic acids. The samples were loaded onto RNeasy columns (Qiagen) and centrifuged for 15 s at 6,000 x g, washed with 700 µl of RW1 buffer, and centrifuged for 15 s at 20,200 x g. Eighty microliters of RD buffer per sample containing 0.34 U of RNase-free DNase (Qiagen) per µl was added, the samples were left to stand for 20 min at 37°C, and the column was then washed twice with 500 µl of RPE buffer and centrifuged for 15 s at 6,000 x g for the first wash and 2 min for the second. RNA was then eluted twice in 50 µl of RNase-DNase-free water (Sigma-Aldrich) by centrifugation for 1 min at 6,000 x g and quantified at an optical density of 260 nm with a Gene Quant II spectrophotometer (Amersham-Pharmacia Biotech, Orsay, France). Any RNA breakdown was detected by ethidium bromide staining after electrophoresis (0.5x Tris-acetate-EDTA) on agarose gel (1.4%, wt/vol). RNAs were judged undamaged when only two sharp bands corresponding to the large and small subunits of rRNA were visible.
Reverse transcription. Immediately after extraction, reverse transcription was performed on 500 ng of RNA by using the Taqman RT reagents kit (Applera) according to the manufacturer's recommendations.
Real-time PCR. The amounts of cDNA obtained by reverse transcription were quantified with the real-time fluorogenic 5' nuclease assay by using an ABI Prism 7000 sequence detector (Applera). We determined the level of transcripts of the lasR gene, which controls both of the QS systems, of the lasB and aprA genes, which are regulated by these QS systems, and of the small-subunit rRNA gene. The probes and primers (Table 1) used to quantify their expression were designed by using the Primer Express ABI Prism program (Applera) and considering the published sequences of lasR, lasB, and aprA. The probes were obtained from Applera and labeled 5' with the 6-carboxyfluorescein fluorescent dye as reporter and 3' with the 6-carboxytetramethylrhodamine as quencher. Amplification was performed in a final volume of 20 µl in MicroAmp Optical plates (Applera). The 20-µl reaction mixture contained 10 µl of cDNA sample diluted 1:20, 1x Taqman buffer A, 5.5 mM MgCl2, 200 µM (each) dATP, dCTP, and dGTP, 400 µM dUTP, 200 nM forward primer, 200 nM reverse primer, 100 nM probe, 0.01 U of uracil-N-glycosylase (AmpErase UNG) per µl, and 0.025 U of AmpliTaq Gold DNA polymerase per ml. Before amplification, the PCR mixtures were heated at 50°C for 2 min to prevent carryover of PCR products and then to 95°C for 10 min to denature nucleic acids. All PCRs were run in duplicate and included 40 cycles (95°C for 15 s and 60°C for 1 min). The evolution of the fluorescent intensity of each dye was recorded continuously by using the ABI Prism 7000 sequence detection system (PE Applied Biosystems). The amount of DNA in the sample was calculated by comparing it with the values obtained with standards comprising 10-fold dilutions of P. aeruginosa DNA ranging from 25 to 0.025 ng/ml (corresponding approximately to 3.8 x 106 to 3.8 x 101 copies per ml of each amplified target). Negative controls consisting of distilled water or total RNA were included in each test to detect DNA contamination. Data were analyzed with Sequence Detector version 16 application software (Applera) on a personal computer linked directly to the ABI Prism 7000 sequence detection system, as recommended by the manufacturer. The mRNA of lasB, aprA, and lasR genes extracted from each strain was normalized on the basis of the small-subunit rRNA levels, which were determined in each of the real-time PCR experiments. Normalization consisted of dividing the number of copies of the larR, aprA, or lasB transcripts by the number for the small-subunit rRNA and multiplying by 1,000. The PCRs for each strain were repeated three times. Analysis of our data indicated that small-subunit rRNA levels were essentially identical at 120 and 300 min of growth for every strain.
Statistical analysis. All analyses were carried out by using the Prism software package (GraphPad Prism software).
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RESULTS |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Overall, there were increases in the levels of lasR transcripts in stationary phase compared with those in early log phase in 33 of the 35 strains (P = 0.01, paired t test), indicating that for most clinical isolates some type of QS response occurred, as reflected by an increase in the lasR transcript level. There was no correlation in the changes in lasR transcript levels based on the genotypic relationship of the lasR gene to the lasR gene of strain PAO1. Two strains isolated from patients with pneumonia had no increase in lasR transcript level. The geometric mean increase in the level of lasR transcripts between 120 and 300 min of growth was 7.1 transcripts per cell, but there was a wide range between a 0.54-fold geometric change (i.e., decrease) and a 17-fold increase. Thus, almost all of the strains showed an increase in lasR transcript levels going from early-log- to stationary-phase growth in vitro.
Interestingly, there were significant differences noted in the levels of lasR transcripts in isolates from different sources (Fig. 1). Overall, the pneumonia isolates had significantly higher levels (P < 0.01) of lasR transcripts at both 120 and 300 min of growth than those of the bacteremia strains. Isolates from the environment, which likely represents the source of most clinical P. aeruginosa isolates, were intermediate in their lasR transcript levels between the other two clinical sources and not significantly different from the strains isolated from these other two sources. It is unclear if this association of clinical source and lasR transcript level is of significance in regard to virulence, as there were no significant differences (P > 0.5) by clinical source in the levels of the LasR-regulated transcripts for lasB or aprA at either 120 or 300 min of growth.
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4.8
transcripts per cell), there was no real correlation with the
transcript levels present in stationary phase (r2
= 0.2, P > 0.05), as shown in Fig.
2A. In contrast, almost all of the correlation between the levels of
lasR transcripts at 120 min and 300 min of growth occurred
with the 17 strains above the initial median level at early log phase
(r2 = 0.83, P < 0.001), as
shown in Fig. 2B. The
geometric mean level of lasR transcripts at 300 min of growth
for the strains with 4.8 transcripts per cell at 120 min of
growth was 5.5 (lower and upper standard error of the mean, 4.1, 7.1)
(P < 0.001 compared with the level at 120 min, as
determined by the paired t test), whereas for strains with
>4.8 lasR transcripts per cell at 120 min of growth
the geometric mean at 300 min of growth was over nine times higher,
38.4 (35.3, 41.6) (P < 0.001 compared with the level
at 120 min, as determined by the paired t test; P
< 0.001 for comparison of the geometric means at 300 min of
both the initial 50% lowest and 50% highest levels of
lasR transcripts). This finding indicates that the initial
level of lasR transcripts in those strains with high
constitutive levels in early log phase strongly influences the
transcript level in stationary phase, whereas for strains with low
constitutive levels the amount of lasR transcript produced in
stationary phase was still low and not correlated with the initial
transcript level.
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0.001, as determined by paired t tests) in
transcript levels for both lasB and aprA genes among
the 35 strains, but there was no correlation between levels at 120 and
300 min of growth. This finding may indicate that factors other than
the initial level of lasB and aprA determined the
level of transcripts in stationary
phase. Analysis of the correlation of lasR transcripts with lasB and aprA transcripts in early log and stationary phases. To determine if lasR transcription was one of the factors influencing levels of lasB and aprA transcripts in both the early log and stationary phases, we performed a variety of linear regression analyses. The level of lasR transcripts at 120 min in all 35 strains analyzed correlated significantly but very modestly with that of aprA in early log phase (Table 4, group A). At 300 min of growth, the level of lasR transcripts for all 35 strains actually correlated less well, but still significantly, with that of aprA (Table 4, group A). There was no correlation between the transcript levels of lasR and lasB at early log phase for any of the 35 strains (Table 4, group A), but in stationary phase there was a reasonably good and significant correlation between these transcript levels (Table 4, group A). Thus, lasB transcript levels at 300 min seemed to be much more strongly influenced by lasR than were those of aprA.
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Analysis of the correlation of lasB and aprA transcripts in early log and stationary phases. Since LasR regulation of the transcription of lasB and aprA in stationary phase was limited to about one-half of the strains as determined by correlation analysis, we sought to determine if there were other factors regulating transcription of lasB or aprA by analyzing the correlation between lasB and aprA transcripts. An analysis of the entire group of 35 isolates revealed a reasonable and significant correlation between the transcript levels of lasB and aprA in stationary phase (Table 4, group A). The correlation at 300 min of growth was present both for strains with lasR transcript levels below the median for the entire population in stationary phase (Table 4, group B) and for strains with lasR transcript levels above the population median at stationary phase (Table 4, group C). Also, there was a modest correlation (r2 = 0.3, P < 0.05) between aprA and lasB transcript levels at 120 min in those strains with lasR transcript levels above the median measured at 300 min. This correlation of lasB and aprA transcript levels with each other for all strains regardless of the lasR level indicates that LasR does not always play a major role in regulating transcription of lasB and aprA.
Other analyses indicated no difference in transcript levels or in correlations for lasR, lasB, or aprA among bacteremia, pneumonia, or environmental isolates. These individual analyses gave essentially the same results as did the analysis done on the entire group of 35 strains.
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DISCUSSION |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Even among comparable laboratory strains of P. aeruginosa there are differences in QS-regulated transcriptional responses. When mutant strains of PAO1 unable to produce endogenous homoserine lactone (HSL) due to deletion of both the lasI and rhlI genes (29) or rhlR and lasR (22) were given exogenous HSL, both studies reported increased transcription of lasB but with a large difference in the magnitude of the transcriptional response. Shuster et al. (22) reported a 110-fold increase in lasB transcription in response to 2 µM N-3-oxododecanoyl-HSL (3O-C12-HSL) and a 180-fold increase in response to a combination of 2 µM 3O-C12-HSL and 10 µM N-butanoyl-HSL (C4-HSL). Wagner et al. (29) reported only a 39-fold increase in lasB transcription in response to 1 µM 3O-C12-HSL plus 2 µM C4-HSL. Both studies also reported increases in aprA transcript levels, with Wagner et al. (29) reporting a 6.9-fold change in response to 1 µM 3O-C12-HSL plus 2 µM C4-HSL, while Shuster et al. (22) found a 25-fold increase in the response of their mutant strain to 2 µM 3O-C12-HSL and a 27-fold increase in response to a combination of 2 µM 3O-C12-HSL and 10 µM C4-HSL. Note that another important difference between these two PAO1 variants is that the strain used by Wagner et al. (29) has also been found to harbor a mutation in the nfxC gene, leading to overexpression of the MexEF-OprN efflux pump (10), which increases antibiotic resistance, decreases virulence, alters cell-to-cell signaling, and decreases transcription of lasB, the latter result being apparent when comparing the transcriptional responses reported by Wagner et al. (29) and Shuster et al. (22).
Since the differences in transcript levels between two otherwise closely related strains with a difference in a gene outside of the QS system were large, it is clear that even small genetic differences that likely occur among the wide variety of clinical and environmental strains of P. aeruginosa can also impact the QS response in many ways. Therefore, it is not surprising that among about one-half of the strains we studied there was very little impact of the QS response that occurs in early stationary phase on the transcription of lasB and aprA.
A functional link between lasR gene transcription and the consequent transcription of the QS-activated genes has been suggested in lung infections associated with CF (5, 25). This link was made by using an approach based on the detection and correlation of gene transcripts in samples of CF sputa. The difficulty with analysis of transcript levels in sputum is that different strains of bacteria in the sputum may be responding to different concentrations of QS signals and thus transcribing different sets of genes at the same time (5, 25). Also, the rapid degradation of mRNA resulting from the interactions between bacterial mRNA and human products present in infected sputa was problematic for quantifying the transcript levels. Thus, it is difficult to use such results for accurate analysis of QS responses during human infection.
Further support for the idea that a QS-based transcriptional response of virulence factor genes modulated by LasR may be present in only about half of P. aeruginosa clinical and environmental isolates came from the analysis of the correlation of the levels of lasB and aprA transcripts. Here, we found that the levels of these transcripts in early stationary phase correlated significantly with each other regardless of the strain's initial or final level of lasR transcripts. Thus, factors other than the lasR transcript level affected transcription of lasB and aprA, and these other factors appeared to have a more common effect among the isolates than did the lasR transcript level. While we cannot fully exclude the possibility that some of these factors may be related to the levels or functions of LasR that are independent of the lasR transcript level, these findings do point out that for about 50% of P. aeruginosa isolates conclusions regarding the role of LasR-dependent QS responses cannot be inferred from lasR transcript levels.
Overall, an extensive analysis of genetic sequences and transcriptional responses of a large set of P. aeruginosa clinical and environmental isolates indicates that the lasR-dependent QS transcriptional response of the lasB and aprA genes may be present in about one-half of the strains. There was no indication of a large amount of allelic variation among the lasR genes, with the vast majority of strains having a nucleotide sequence very close or identical to that of PAO1. Differences were noted principally between the strains with low and high constitutive levels of lasR transcripts in early log phase. Strains with levels above the median for 35 isolates tended to produce more lasR transcripts in stationary phase, with a strong correlation between the initial and final levels. These strains also had the better correlation of lasR transcripts with lasB and aprA, although for the latter, the correlation, while significant, was weak. For strains with lasR transcript levels below the median for the population, there was little increase in lasR transcripts in stationary phase and no correlation with the transcription of lasB or aprA genes. Given that many of these strains were, nonetheless, clinical isolates, it appears that among non-CF isolates of P. aeruginosa the lasR-dependent transcriptional activation of lasB and aprA is present in only one-half of strains and thus unlikely to contribute significantly to virulence in these strains. Finally, as we did not analyze protein levels, we cannot exclude the possibility that there was, nonetheless, production of LasB and AprA among the strains with low transcript levels that was comparable to that of strains with high transcript levels. But as the molecular aspects of the LasR-QS system have been defined by microarray analysis (22, 29) and correlative analysis of transcript levels, particularly in CF (5, 25), this study shows that correlations among the lasR, lasB, and aprA transcripts may be found in only about 50% of clinical strains of P. aeruginosa.
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ACKNOWLEDGMENTS |
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This work was supported in part by a grant from the Ministère de l'Education Nationale de la Recherche et de la Technologie: réseau infections nosocomiales à Pseudomonas aeruginosa and by a grant from Université Paris VII, Faculté X. Bichat: BQR.
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FOOTNOTES |
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REFERENCES |
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