wild-type strain PAO1 (7
) was used for biofilm and planktonic culture expression analysis. Overnight cultures were grown in LB broth (37°C, 200 rpm). Three separate RNA samples were extracted under each condition. Therefore, three biological replicates were used, and data from triplicate arrays were obtained for each condition. For biofilm samples, five filters were removed for each RNA extraction after 8, 14, 24, and 48 h. Immediately after removal from the agar surface, filters were placed directly into TRIzol reagent (Invitrogen) and cells were removed from each filter by scraping with a sterile loop. For planktonic RNA samples, 100 ml LB (20%) broth in 250-ml Erlenmeyer flasks was inoculated with 1 ml PAO1 overnight LB culture (diluted 10-fold), and the resulting cultures were grown at 37°C with agitation (200 rpm). After 4-h (optical density at 600 nm [OD600
], 0.1) (LP) and 24-h growth (OD600
, 0.3) (SP), 25-ml aliquots were pelleted by centrifugation (5 min, 8,000 rpm, 4°C). Cells were then resuspended in TRIzol reagent (Invitrogen). All samples (planktonic and biofilm) were subjected to vortexing and sonication before chloroform extraction and isopropanol precipitations were carried out. RNA pellets were then washed with 70% ethanol and resuspended in water. Residual DNA was then removed by use of a DNA-free kit (Ambion) and RNA of <200 nucleotides removed by use of an RNeasy (QIAGEN) RNA extraction kit. The quantity and purity of RNA were calculated through OD260/280
spectrometry and agarose (1%) gel electrophoresis. cDNA synthesis (from 11 μg RNA), hybridization, and scanning were performed according to the manufacturer's instructions for the P. aeruginosa
GeneChip array (Affymetrix).
All data were globally scaled to set the average signal intensity of each array to a target signal of 100. Data analysis and normalizations were performed by using GeneSpring software (version 5.1; Silicon Genetics). For comparisons between two different conditions, genes that displayed an expression value of under 50 (considered background) for all replicates were removed. By use of the expression data from all six conditions (four biofilm time points and two planktonic phases), an experiment tree was drawn by using GeneSpring software (version 5.1; Silicon Genetics) (Fig. ). This shows the relationships between the expression levels of the six different conditions and clusters together conditions with similar expression profiles. This procedure clustered the LP planktonic culture with the 8-h-time point developing biofilm, whereas the SP planktonic culture clustered with the confluent biofilms formed at the 14-, 24-, and 48-h time points. Quantitative reverse transcriptase PCR of four genes (fliE, PA0020, PA2184, and PA5555) was used to provide independent verification of the microarray results (data not shown).
FIG. 2. Microarray data experiment tree (drawn using GeneSpring version 5.1 [Silicon Genetics]) with data from six different conditions. LP, log-phase planktonic culture; SP, stationary-phase planktonic culture. Numbers (8, 14, 24, and 48) refer to biofilm at (more ...)
In order for a gene to be considered to be differentially expressed, two criteria had to be fulfilled: the average change in expression (n-fold) must be ≥2.5 and P values must be <0.05 (one-way analysis of variance). Table illustrates that 19.4% of the PAO1 genome is differentially expressed (10.5% genes up-regulated and 8.9% genes down-regulated) when gene expression in LP planktonic culture is compared with that in SP planktonic culture. However, when gene expression in LP planktonic culture is compared with gene expression in 8-h developing biofilms, only 3.1% of the genome is differentially expressed (0.8% genes up-regulated, 2.3% genes down-regulated), and when SP planktonic culture gene expression is compared with gene expression of 14-, 24-, and 48-h confluent biofilms, ≤14.3% of the genome is differentially expressed. However, gene expression among the confluent biofilm time points (14, 24, and 48 h) was found to be very conserved (<1% of genes are differentially expressed) (Table ), whereas gene expression in developing biofilms (8 h) differs considerably from the confluent biofilms (14, 24, and 48 h), as at least 15.5% of genes are differentially expressed.
Percentages of genes differentially expressed when two conditions are compared
Recent advances in genomics and proteomics have accelerated our understanding of the physiology of biofilms, but two recent studies have yielded conflicting data (17
). A microarray study in which gene expression in strain PAO1 biofilms grown on stones in a chemostat was compared with that of a chemostat planktonic population unexpectedly showed that only 1% of the genome was differentially expressed (28
). Conversely, in a recent PAO1 proteomic study, the difference in proteomes was >50% when a mature 6-day biofilm grown inside silicone tubing was compared to a planktonic culture (17
). Protein patterns from different stages of biofilm development were also found to be profoundly different (17
). Recently, a gene expression study using Escherichia coli
Affymetrix DNA arrays compared a single biofilm stage with LP and SP planktonic cultures (18
). When biofilm gene expression was compared with that obtained in LP planktonic culture, 4.8% of genes were up-regulated (≥2.5-fold change) and 0.63% were down-regulated, whereas a comparison with SP planktonic culture found 9.7% of genes were up-regulated and 4.48% were down-regulated (18
). Another E. coli
biofilm microarray study using a different strain compared a mature biofilm and LP planktonic culture and found that 1.9% of the genome was up- or down-regulated by a factor of 2 or more (2
). Considering these P. aeruginosa
and E. coli
studies, together with the results from our study, this emphasizes the importance of comparing transcriptomic profiles of more than one planktonic state of growth with more than one biofilm structure. These studies also highlight the fact that differential gene expression between biofilm and planktonic culture will also differ among strains, culture conditions, and technologies used (glass slide array, GeneChip array, and proteomics) and that more of these studies are needed in order for us to fully understand the genetics of bacterial growth.