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Multivariate Approach to Comparing Whole-Cell Proteomes of. Bacillus cereus Indicates a Biofilm-Specific Proteome. Se´bastien Vilain and Volker S. Br...
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Multivariate Approach to Comparing Whole-Cell Proteomes of Bacillus cereus Indicates a Biofilm-Specific Proteome Se´ bastien Vilain and Volker S. Bro1 zel* Department of Biology and Microbiology, South Dakota State University, Brookings, South Dakota 57007 Received November 14, 2005

Biofilm bacteria are widely held to exhibit a unique phenotype, typified by their increased resistance to antimicrobial agents. Numerous studies have been devoted to the identification of biofilm-specific genes, but surprisingly few have been reported to date. We compared the whole cell proteomes of 24 h old Bacillus cereus biofilms and the associated suspended population to exponential, transient and stationary phase planktonic cultures using the unbiased approach of principal component analysis, comparing the quantity variations of the 823 detected spots. The analyses support the hypothesis that biofilms of Gram positive bacteria have a unique pattern of gene expression. The data provides proteomic evidence for a new biofilm and surface influenced planktonic population which is distinct to both planktonic and biofilm cells. Keywords: Bacillus cereus • biofilm • glass wool • proteome • principal component analysis

Introduction Biofilm formation appears to be a universal feature of microbes.1 Many bacterial species are able to colonize a range of substrata and other interfaces in both wet and humid environments. The adherent cells become attached, grow, and divide to form microcolonies, and often become encased in an extracellular matrix.2,3 Further growth of microcolonies leads to the development of multicellular biofilms. Members of the biofilm population exhibit specific characteristics, most prominently very high resistance to antimicrobial agents such as biocides and antibiotics.4 Some have argued for a specific biofilm physiology for these sessile cells,5,6 but current evidence for a biofilm-specific resistance phenotype is restricted to the finding of ndvB involved in the synthesis of cytoplasmic glucans by Pseudomonas aeruginosa.7 Others have proposed that this unique physiology occurs in a sub-population of so-called persister cells due to an altered pattern of gene expression in some biofilm cells.8 Both models imply the appearance of a specific biofilm phenotype and therefore a specific proteome. Such a biofilm-specific proteome was recently described in Pseudomonas aeruginosa,9 the primary Gram negative model organism for studying bacterial biofilms. The biofilm phenotype of P. aeruginosa appears regulated more at the translational and perhaps post-translational level than at the transcriptional level, as highlighted by the discrepancy between results of microarray and proteomic experiments. A study of the P. aeruginosa biofilm and planktonic transcriptome revealed a difference of less than 1% in gene expression, leading some to speculate that biofilms are simply a mass of bacteria at various stages of growth.10,11 The proteomic approach has revealed a difference between biofilm and plank* To whom correspondence should be addressed. Tel: (605) 688-6483. Fax: (605) 688-5624. E-mail: [email protected].

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Journal of Proteome Research 2006, 5, 1924-1930

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tonic populations of up to 38%.12 Global transcriptomic and proteomic analyses are clearly subject to some level of error due to sample extraction, handling and processing, but such variability could not account for the observed discrepancy.13 The Pearson correlation coefficients between proteomic and transcriptomic data are between 0.46 and 0.76 in yeast,14 highlighting the greater degree of differences as revealed by proteomic vs transcriptomic approaches. Proteomic analysis would therefore constitute a more appropriate approach to analyzing the biofilm phenotype. The focus of biofilm research has been directed to the Gram negative bacteria, primarily P. aeruginosa, leading to continuous refinement of the model for biofilms of this group of bacteria. A variety of biofilms of Gram positive bacteria have been studied by genomic and proteomic approaches, including Listeria monocytogenes,15,16 Bacillus subtilis,17 Streptococcus mutans,18 Staphylococcus aureus,19 and B. cereus DL5.20 While all these studies have demonstrated differential expression of specific genes at either the transcriptional or translational level, a rigorous statistical approach to proteomes of biofilms of Gram positive bacteria is lacking. Members of the Gram positive aerobic spore-forming genus Bacillus occur in a range of environments, from soil to food and dairy processing surfaces.21,22 Bacillus cereus group members are among the more commonly observed species.23 B. cereus sensu lato comprises the species B. cereus, B. anthracis, B. thuringiensis, B. mycoides, B. pseudomycoides, and B. weihenstephanensis.24,25 B. cereus is widely reported as a soil bacterium that contributes to food spoilage, and is occasionally an opportunistic human pathogen.26,27 It readily forms biofilms on a range of surfaces.20,28 Culturing platforms for biofilms have been refined and standardized for genetic and microscopic investigations,29 but proteomic studies have necessitated the development of plat10.1021/pr050402b CCC: $33.50

 2006 American Chemical Society

Whole-Cell Proteome of Bacillus cereus Biofilm

forms which yield larger amounts of biomass for protein extraction. One approach entails using Tygon or silicone tubing fed with a continuous stream of sterile medium,30 yielding a biofilm grown under quasi steady-state conditions and devoid of any surrounding suspended cells. Glass wool in batch systems has been used to study P. aeruginosa,31,32 Escherichia coli,33 Bacillus subtilis,22 and B. cereus.34,20 The glass wool is placed into Erlenmeyer flasks, so that the inoculated population grows as a batch culture, distributing into attached and freeliving sub-populations. The planktonic population is therefore a temporal mixture of sub-populations of free-living cells, cells that were recently attached reversibly, and cells detached from the biofilm. Conversely, the biofilm will increase in numbers due to both division of attached cells and recruitment of cells from the suspended population. This scenario resembles biofilms in the environment more closely than the oncethrough flow systems as few naturally occurring surfaces are bathed with sterile liquids containing a full complement of nutrients. Rather, biofilms in the environment are surrounded by liquids containing microbial populations. The aim of this work was to employ proteomics to investigate whether biofilms of B. cereus have a unique phenotype, or are a mixture of exponential and stationary phase planktonic populations. Our study was conducted using an unbiased approach by including quantities of all detectable protein spots, rather than reducing the analysis to the quantities of specific identified protein spots. We prepared and analyzed proteome maps of whole cell extracts of planktonic and biofilm populations of Bacillus cereus ATCC 14579 growing in LB at 30 °C by high-resolution two-dimensional electrophoresis (2-DE). Wholecell proteomes were analyzed by multivariate statistics to compare proteomes as complete entities rather than focusing on modifications in the levels of specific spots. Here, we report the first statistical evidence of the existence of a biofilm-specific proteome for a Gram positive bacterium. Moreover, our data show that this specific proteome was not the result of a mixture of exponential and stationary phase planktonic cells. We also report proteomic evidence for a biofilm and surface exposed planktonic (BSP) population which is different to those of both biofilm and planktonic cultures.

Materials and Methods Bacterial Strain; Planktonic Cells and Biofilm Growth Conditions. Bacillus cereus ATCC 14579 were cultured as planktonic cells in a 250 mL Erlenmeyer containing 100 mL of Luria-Bertani (LB) broth (pH 7.0) (Fisher Biotech). Broths were inoculated to a density of 105 CFU/mL using a calibrated inoculum from an overnight culture, and incubated at 30 °C while shaking at 200 rpm. One-day old biofilms of B. cereus were developed on glass wool (GW) fibers by adding 2 g of GW to the Erlenmeyer as previously described by Oosthuizen et al.34 The density of the GW used in this study was experimentally estimated to 2237.5 kg‚m-3 which for a mean diameter of 26 µm indicates a surface of 686 cm2 per gram of GW. Prior to utilization, GW was washed and sterilized twice in water by autoclaving (120 °C, 20 min). The planktonic cells growing in the presence of GW were named Planktonic with Glass Wool (PGW). Harvesting of Bacterial Populations. Planktonic biomass was harvested at mid-exponential phase (140 min, Figure 1), transient phase (the point of transition between exponential and stationary phase, or after 340 min) and stationary phase (24 h), whereas PGW and biofilm populations were harvested

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Figure 1. Growth curves of planktonic, PGW and attached Bacillus cereus ATCC 14579 cells growing in LB broth at 30 °C. Planktonic cells (9) were harvested from an Erlenmeyer without GW (data expressed as CFU/mL), PGW (0) corresponded to planktonic cells growing in the presence of GW (data expressed as CFU/mL) and sessile cells (2) were collected from the glass wool (data expressed as CFU/cm2). Arrows mark harvesting point for all 2-DE samples. Abbreviations: Exp for Exponential phase, Tr for transient phase, Stat for stationary phase, GW for biofilm on glass wool, and PGW for planktonic with glass wool.

at 24 h. Planktonic and PGW cells were collected by centrifugation (12 000 × g for 15 min), and pellets were washed twice in sterile phosphate buffer (100 mM, pH 7.0). For biofilm populations, GW was removed from the Erlenmeyer and gently washed in phosphate buffer. Then, adhering cells were harvested by shaking for 5 min in the presence of 30 g of glass beads (Fisher Scientific, Ø ) 2 mm) and 20 mL of phosphate buffer. The liquid phase was collected and the biomass harvested by centrifugation (12 000 × g for 15 min). Pellets were washed twice in phosphate buffer and resuspended in either phosphate or lysis buffer. Quantification of Biomass. The growth of planktonic and PGW cells was characterized by determining vegetative cell and spore densities as colony forming units (CFU) per mL by using the droplet technique.35 Serial dilutions (10-1 to 10-7) were prepared in sterile phosphate buffer (100 mM, pH 7.0) and 20 µL volumes of each dilution were spotted onto LB agar plates. Plates were incubated at 30 °C for 10 h, when colonies were counted. Spore densities were determined by pasteurizing serial dilutions at 80 °C for 10 min prior to plating. The droplet technique was also used to estimate biofilm cell counts as CFU/ cm2 of GW. After harvesting of adherent biomass, the number of CFU/cm2 was obtained by using the formula: CFU/cm2 ) (n ÷ d × 50 × V)/(686 × 2); where: n is the number of colony counted on the plate, d is the dilution of the used tube, V is the volume of suspension after harvesting (i.e., 20 mL + volume remaining adherent to GW after it had being washed in phosphate buffer). All determinations were performed on three separate samples. Microscopic Investigation. Bacteria in one-day old biofilms were visualized by the Live/Dead BacLight stain (Molecular Probes, L7012). GW fiber samples were stained directly on glass slides by applying the nucleic acid stains SYTO 9 and Propidium iodide (diluted 1/1000 in phosphate buffer) and incubated for 15 min. Biofilms were viewed by confocal scanning laser microscopy (CSLM) using an Olympus Fluoview FV300 Laser Scanning Confocal microscope System interfaced with an inverted-microscope (Olympus IX70) using Blue Argon (488 nm) and Green Helium Neon (543 nm) excitation lasers. Journal of Proteome Research • Vol. 5, No. 8, 2006 1925

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Table 1. Total Culturable Count (CFU) of Planktonic, PGW and Biofilm Populations in the Respective Erlenmeyer Containing 100 mL LB Broth

a

time (h)

planktonic

PGW + sessile cells

% sessile cells

% sporesa

0 2 4 6 8 12 16 24

(1.00 ( 0.00) × 107 (2.61 ( 0.34) × 108 (1.66 ( 0.11) × 1010 (5.38 ( 0.24) × 1010 (4.25 ( 0.43) × 1010 (3.88 ( 0.66) × 1010 (4.38 ( 0.47) × 1010 (4.00 ( 0.71) × 1010

(1.00 ( 0.00) × 107 (3.54 ( 0.21) × 108 (1.45 ( 0.14) × 1010 (4.21 ( 0.52) × 1010 (4.54 ( 0.51) × 1010 (5.56 ( 0.25) × 1010 (5.33 ( 0.37) × 1010 (3.91 ( 0.92) × 1010

0.00 ( 0.00 13.15 ( 0.64 2.89 ( 0.20 2.12 ( 0.13 3.83 ( 0.43 3.41 ( 0.09 3.79 ( 0.42 12.59 ( 1.53

0.00 ( 0.00 0.00 ( 0.00 0.00 ( 0.00 0.00 ( 0.00 0.00 ( 0.00 0.00 ( 0.00 0.00 ( 0.00 0.00 ( 0.00

Exponential, transient and stationary phase populations. Data are presented as the mean ( SEM (n ) 4).

Table 2. Summary of the Principal Component Analyses. Abbreviations Are as Described in the Caption to Figure 1 figure

matrix with

3B

exp, Tr, Stat, PGW, GW

4A

exp, Tr, Stat, GW

4B

exp, Stat, GW and in silico mixtures

5A

exp, Tr, Stat, PGW

5B & C

exp, Stat, GW, PGW and in silico mixtures

Preparation of Protein Extracts. Bacterial pellets were resuspended in 2 mL of iso-electrofocusing (IEF) buffer of the following composition: Ampholytes 3-10, 2% (v/v); Urea, 7 M; Thiourea, 2 M; CHAPS (3-[3-chloamidopropyl)dimethylammonio]-1-propanesulfonate), 2% (w/v); ASB-14, 2% (w/v) and dithiothreitol, 10 mM. Cells were disrupted by thermal shock (from -80 °C to 20 °C) followed by ultrasonication (Sonifier 150, Branson Ultrasonics Corporation) at 4 °C (20 W; continuous 2 min). Then, samples were centrifuged (12 000 × g for 15 min) to eliminate cell debris. The amount of protein in the supernatant was determined using the Bio-Rad protein assay. The protein samples were stored at -80 °C. Two-Dimensional Gel Electrophoresis. The first dimension gel separation was carried out using Immobiline Dry Strips (18 cm, linear pH gradient 4-7, Amersham Biosciences). A 50-µg portion of protein was supplemented with IEF buffer to a final volume of 400 µL. Coomassie Brilliant Blue R250 was used as indicator of migration and due to its effect on focusing.36 The first dimension was performed using the following parameters: 150 V for 1 h, 350 V for 1 h, 500 V for 4 h, 750 V for 1 h, 1 kV for 1 h, 1.5 kV for 1 h and 3.5 kV for 11 h (3 mA max) for a total of ∼ 44 kVh. The second dimension consisted of SDSPAGE using a 12.5% (w/v) running polyacrylamide gel and a 4.65% stacking gel (width, 18 cm; length, 20 cm; thickness, 1 mm). After migration, proteins were visualized by a mass spectrometry compatible silver nitrate stain.37 Construction of Proteomic Maps. Three two-dimensional electrophoresis (2-DE) gels, each prepared using a distinct extract, were prepared for each bacterial population. Gels were scanned using ScanMaker 9800XL (Microtek) in transmission mode and analyzed using the PDQuest software (version 7.3.1, Bio-Rad), which allows detection, quantification and matching of protein spots. Spots were quantified on a Gaussian image and pooled on a reference image. The following formula was 1926

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component

eigenvalue

% of variation

cumulative %

1 2 3 4 1 2 3 4 1 2 1 2 3 1 2 3

1.870 14 1.360 69 0.997 88 0.771 29 1.753 05 1.190 30 0.877 47 0.179 18 3.576 94 2.423 06 1.911 43 1.165 21 0.923 36 8.151 57 6.559 21 1.289 22

37.403 27.214 19.958 15.426 43.826 29.758 21.937 4.479 59.616 40.384 47.786 29.130 23.084 50.947 40.995 8.058

37.403 64.617 84.574 100.000 43.826 73.584 95.521 100.000 59.616 100.000 47.786 76.916 100.000 50.947 91.942 100.000

used to calculate the quantity of Gaussian spot: Spot height × σx × σy × π; where: spot height is the peak of the Gaussian representation of the spot, σx is the standard deviation of the Gaussian distribution of the spot in the direction of the x axis, and σy is the standard deviation in the direction of the y axis. Data Processing and Statistical Analysis. A total of 823 spots were selected because of their reproducibility across the 5 proteomic maps (exponential phase, transient phase, stationary phase, biofilm, and PGW) used in this study. A spot was classified as reproducible if it was observed on each of the 3 experimental gels used to perform the proteomic map of a specific population. This enabled us to build a database of 15 columns (global proteome according to the growth condition) and 823 lines (individual spot quantities across the different growth conditions) resulting in 12 345 distinct quantities (Microsoft Excel 2002). This database was reduced by using the mean quantity for each spot from each growth condition (5 columns by 823 lines). From the database, five different matrices were prepared. Three matrices were prepared using data from experimental proteomes, and a further two matrices were prepared using a combination of experimental and in silico proteomes (Table 2). The in silico proteomes corresponded to hypothetical proteomes of various mixtures of populations. Thus, a spot having a value equal to X in experimental proteome A, and Y in experimental proteome B will have a value of 0.75 × X + 0.25 × Y in a mixture of 75% A/25% B. One matrix comprised data from GW and various mixtures of Exponential/ Stat; and another of PGW and various mixtures of Exponential/Stationary/GW. Stagraphics Plus 4.0 (Manugistics) was used to perform Principal Component Analysis (PCA) and Cluster Analysis with vertically and horizontally standardized data (i.e., converted to normal scores).

Whole-Cell Proteome of Bacillus cereus Biofilm

Figure 2. Bacillus cereus biofilm on a glass wool fiber cultured for 24 h in LB broth at 30 °C. Cells were stained by Live/Dead BacLight stain and visualized by confocal scanning laser microscopy. Cells appearing white/light gray fluoresced green and all other cells and their surrounding appeared red.

Results and Discussion Growth Characteristics of Biofilm and Planktonic Cells in Batch Culture. B. cereus formed two growing populations in flasks with glass wool, with some cells occurring as part of biofilms and the majority being free-living in the presence of an attachment surface. We have termed this free-living population planktonic with glass wool (PGW). The number of cells in biofilms increasing exponentially (Figure 1) to form densely packed biofilm on the glass wool (Figure 2). Yet the majority of cells in flasks with glass wool occurred in suspension (PGW), with 13% of cells attached at 2 h post inoculation. The attached population increased more slowly in numbers than did the PGW population, dropping off to ca. 3% by 4 h. By 24 h the biofilm population had increased proportionally to constitute 12.6% of the total population (Figure 1, Table 1). The nucleic acid stains in the Live/Dead BacLight stain are widely used to differentiate between living (Syto 9, green fluorescence) and dead cells (Propidium iodide, red fluorescence). While culturing data indicated net growth over the 24 h period, the bulk of biofilm cells appeared red. Closer inspection by CSLM revealed strong extracellular and cell wall-associated red fluorescence (Figure 2). Further experiments involving DNase treatment have confirmed the presence of extracellular DNA (data not shown), leading to masking of intracellular green by red fluorescence, making cells appear dead. An increase in the PGW population would be ascribed either to growth or detachment of cells from the biofilm, while a proportional increase in the attached population implies a net biofilm gain, due either to growth or recruitment from the suspended population. This restricted propensity to form biofilm is similar to the distribution observed for Pseudomonas aeruginosa,31 but much lower than reported previously for B. cereus DL5 isolated from a dairy cleaning solution.20 The average biofilm density corresponded to 3 × 106 CFU/cm2 (Figure 1). This cell density is lower than the 1.7 × 108 CFU/cm2 found for B. cereus DL520 and 3.4 × 107 CFU/cm2 for Salmonella weltevreden on plastic (48 h, 28 °C),38 but is much higher than the 6 × 102 CFU/cm2 reported for Listeria monocytogenes growing on stainless steel (24 h, 30 °C).39 The PGW population grew essentially as the planktonic population (generation time ) 26 min) and to the same final yield, showing that the biofilm did not adversely affect cell division or survival (Figure 1). The presence of glass wool and concomitant biofilm did not significantly increase the total cell number in a flask (Table 1) as the biofilm biomass constituted

research articles a small percentage of the total biomass per flask. For all time points between 0 and 24 h, no significant difference was observed between total culturable counts in flasks with and without GW (t-test, υ ) 6, R ) 0.05). The maximum observed was ca. 4 × 1010 CFU at 24 h. No spores were detected in any population during the 24 h of incubation by the pasteurization method (Table 1). This is in agreement with reports of the apparent suppression of sporulation observed in rich culture media.40 Proteomic Characteristics of Planktonic, Biofilm and PGW Populations. The protein extracts of the three planktonic populations, and of 24 h biofilm and associated PGW populations were subjected to two-dimensional electrophoresis. A total of 823 spots were detected across the 5 bacterial populations and quantified by scanning densitometry. This represents 15% of the 5390 predicted open reading frames of B. cereus ATCC14579,25 being a significant improvement on a previous analysis of B. cereus DL5 biofilm where 345 spots were detected.20 To compare more comprehensively the physiological states of the various populations, a nonreductionistic approach was taken. Rather than reducing the comparative analysis to the quantities of specific identified protein spots, all detectable spots were included in the analysis. Principal Component Analysis (PCA), a non parametric multivariate analysis, allows a graphic visualization of the correlation between variables by grouping or discriminating them according to axes of principal components.41 PCA was used to interpret spot mean quantity variations in the context of the following two questions: 1. Are biofilms comprised of a mixture of cells at various stages of growth, corresponding to a mixture of exponential, transient, and stationary phase cells, or do they exhibit a unique proteome and therefore a unique phenotype? 2. Do planktonic cells exhibit a similar proteome when grown in the presence or absence of biofilm (PGW), or are planktonic populations grown in the presence of a biofilm like biofilm cells? To improve the separation of the observations by PCA and render them independent of the absolute amount of protein present in each of the 823 spots, spot quantity values were standardized horizontally (i.e., converted to normal scores). The PCA results of the matrices performed are summarized in Table 2. Cluster analysis of the five experimental proteomes, performed using squared Euclidean distance and complete linkage clustering (furthest neighbor method) to maximize dissimilarities between clusters, revealed two major groups (Figure 3A). The first group included the exponential and transient phase planktonic populations while the second was composed of the three stationary phase cultures. This second group discriminated strongly between suspended and biofilm populations. The Gram negative P. aeruginosa also displays a unique proteome when growing as a biofilm on glass wool as opposed to in suspension.9,32 The squared Euclidean distance between 24 h biofilm and planktonic populations of B. cereus was 1800, 6-fold the distance between 18 h biofilm and planktonic populations of P. aeruginosa.32 This indicated that B. cereus undergoes a greater degree of change when forming biofilm than does P. aeruginosa. The PCA extracted 2 principal components with eigenvalues greater than 1 (Kaiser Criterion)42 from standardized values, collectively accounting for 64.6% of the variability in the data (Figure 3B). The first component confirmed cluster analysis by Journal of Proteome Research • Vol. 5, No. 8, 2006 1927

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Figure 3. Multivariate Analysis of whole cell proteomes of exponential (Exp), transient phase (Tr), stationary phase (Stat), biofilm (GW), and PGW populations cultured in LB broth at 30 °C. (A) Dendrogram deduced from Cluster Analysis of the 5 proteomes (variables). The furthest neighbor method, squared Euclidean distances, and standardized variables were used. (B) Principal Component (PC) Analysis (PCA) of the 5 proteomes presented as biplot of spot quantity standardized scores (0) and population loadings (vectors, 9).

discriminating populations based on age. Component 1 may therefore correspond to the incubation period, which appeared to be the main parameter controlling spot quantity variation in the proteomic maps. The second component discriminated between biofilm cells and all suspended populations, based on 27% of the proteomic modifications. This data supports the hypothesis that biofilm of the Gram positive bacterium B. cereus has a unique proteome and therefore a unique phenotype. Growth mode was the primary parameter controlling protein spot quantity variations in P. aeruginosa,9 but an exponentially growing planktonic population was not included in that analysis. Culture age was the primary parameter distinguishing between populations of B. cereus, raising the question whether the apparent specificity of the biofilm proteome was not due to a mixture of planktonic cells at different stages of growth. This objection has been raised specifically based on transcriptomic data.43,44 Biofilm is not Merely a Mixture of Planktonic Populations. To test whether the biofilm population was merely composed of a mixture of planktonic stages, a second PCA was performed to compare the biofilm specifically with the exponential, transient, and stationary planktonic populations (Figure 4A, Table 2). This PCA extracted 2 components accounting together for 73.6% of the variability in the data (Figure 4A). Component 1 again corresponded to the culture age. Component 2 discriminated between biofilm and stationary populations, as well as between transient and exponential populations. The intervariable angles between vectors representing biofilm and stationary phase, and between biofilm and exponential phase populations demonstrated that the biofilm proteome was significantly not correlated to exponential and stationary phase proteomes. Moreover, the biofilm and transient phase proteomes were diametrically opposed compared to the center, indicating a significant negative correlation (Figure 4A). The two components and the relative position of each variable supported the hypothesis that B. cereus biofilm constitutes a distinct proteome. A second approach to interrogate the planktonic and biofilm proteomes entailed the inclusion of in silico proteomes of various mixtures of exponential and stationary populations in a PCA of biofilm, exponential and stationary populations (Figure 4B). Transient phase data were excluded from this PCA because of the negative correlation with biofilm cell proteomes (Figure 4A). The PCA extracted 2 components with eigenvalues greater than 1, accounting together for 100% of the variability (Figure 4B). Component 1 distinguished between mixtures with 1928

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Figure 4. Principal Component Analysis contrasting the biofilm proteome with stages of the planktonic proteome. (A), biplot of spot quantity standardized scores (0) and population loadings (vectors, 9). (B), Component plot showing separation of in silico proteomes of various mixtures of Exp and Stat (b) with experimental proteomes of biofilm (GW), Exp and Stat (9).

50% or more of exponential data and all other proteomes. Component 2 discriminated primarily between planktonic and biofilm growth modes. This result emphasized the results from the previous comparisons. The diametrical opposition between the biofilm proteome and the mixture of 50% exponential and 50% stationary phase highlighted that biofilms are not composed merely of a mixture of planktonic cells at different growth phases. These results do not prove that proteins contributing to the specificity of the biofilm proteome are expressed solely in biofilm. Rather, they support the notion that biofilms have a unique pattern of gene expression where sets of genes expressed or repressed under different planktonic conditions are expressed simultaneously in biofilm.44

Whole-Cell Proteome of Bacillus cereus Biofilm

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PGW Population is not Merely a Mixture of Biofilm and Planktonic Cells. Biofilms have been widely compared to planktonic populations. Yet few studies have attempted to include suspended populations occurring in the vicinity of the biofilm, termed PGW in this communication. Steyn et al.31 reported that PGW (SIP) populations of P. aeruginosa grown for 18 h in a minimal medium in the presence of glass wool differed from the planktonic counterpart. The proteome of a PGW population of B. cereus DL5 grown in rich medium was distinct, but differed to a lesser degree from its planktonic counterpart. We performed PCA with PGW, exponential, transient and stationary phase proteomes in order to investigate possible differences between planktonic and PGW populations (Figure 5A). The PCA extracted 2 components with eigenvalues greater than 1, accounting together for 77.0% of the variability in the data (Figure 5A & Table 2). Again, component 1 corresponded to the culture age. Component 2 discriminated PGW and stationary phase proteomes on one hand, and transient and exponential proteomes on the other. The intervariable angles between the component vectors indicated that the PGW proteome was not correlated to the exponential proteome. Moreover, the PGW and transient phase were significantly negatively correlated (Figure 5A). The PGW population may constitute an assemblage of freefloating and recently detached biofilm cells, but may also include cells recently attached reversibly to the glass surface. To investigate whether the apparently unique PGW proteome could be the result of a mixture of planktonic and biofilm cells, we performed PCA with PGW, biofilm, exponential, stationary phase and in silico proteomes of various mixtures of the above (Figure 5B,C). PCA extracted 3 principal components with eigenvalues greater than 1 (Table 2), accounting collectively for 100% of the variability. Component 1 opposed mixtures with 50% or more of exponential to all other proteomes, thereby discriminating between in silico populations based on age. Component 2 discriminated between stationary phase planktonic and PGW on one hand, and biofilm influenced proteomes on the other, and was not influenced by the exponential proteome. This second component could therefore be interpreted as representing planktonic vs attached mode of growth. The third component discriminated between the PGW proteome and all others (Figure 5C). B. cereus DL5 and P. aeruginosa studied under similar conditions also displayed a PGW proteome distinct from its planktonic and biofilm counterparts by expressing some unique protein spots.20,31 Component 3 of this PCA offered evidence that the PGW phenotype was not the result of a mixture of released biofilm and stationary phase planktonic cells. Rather, these planktonic cells constituted a unique phenotype, expressed as response to either the proximal biofilm or periodic contact with the glass surface. P. aeruginosa detached from a biofilm display a phenotype distinct to biofilm cells.45 The PGW population at 24 h was unlikely to contain a large proportion of recently detached cells as the biofilm constituted less than 10% of the numbers until 16 h, then increasing by 24 h (Table 1). The bulk of the PGW population was therefore a mixture of free-living cells, and those that had transiently associated with a surface, the so-called reversibly attached cells. We therefore propose to call this suspended population occurring in the vicinity of a surface Biofilm and Surface exposed Planktonic or BSP. The identification of proteins contributing to the specificity of the PGW proteome could shed light on factors contributing to the

Figure 5. Analysis of the 24 h PGW proteome by Principal Component Analysis. (A) Biplots of spot quantity standardized scores (0) and population loadings (vectors, 9) of PGW and exponential (Exp), transient (Tr) and stationary phase (Stat) planktonic proteomes. (B & C) Component plot showing the position of the PGW proteome respective to experimental proteomes (9) and in silico proteomes (b) of various mixtures of Exp, Stat and GW according to PC1 and PC2 (B) or PC1 and PC3 (C). 1, Exp; 2, Stat; 3, GW; 4, PGW; 5, [1/4 Exp, 3/4 GW]; 6, [1/4 Exp, 3/4 Stat]; 7, [1/2 Exp, 1/2 GW]; 8, [1/2 Exp, 1/2 Stat]; 9, [3/4 Exp, 1/4 GW]; 10, [3/4 Exp, 1/4 Stat]; 11, [1/4 Stat, 3/4 GW]; 12, [1/2 Stat, 1/2 GW]; 13, [3/4 Stat, 1/4 GW]; 14, [1/4 Exp, 1/4 Stat, 1/2 GW]; 15, [1/4 Exp, 1/2 Stat, 1/4 GW]; 16, [1/2 Exp, 1/4 Stat, 1/4 GW].

apparent separateness of the two populations occurring in an otherwise identical environment. Biofilm Phenotype in Context. A significant body of evidence now documents the unique phenotype of biofilm populations. This biofilm phenotype includes the production of extracellular polymeric substances which contribute to retaining cells as part of the biofilm,46 enhanced resistance to antimicrobial agents,5 and contribution to microbially influenced corrosion.47 Yet the nature of the specific underlying regulation and expression profiles is not clear at present, and no biofilm specific master regulator has been found.43 Evidence Journal of Proteome Research • Vol. 5, No. 8, 2006 1929

research articles for biofilm specific genes is largely lacking, as most genes found important for biofilm development are known to be important for growth or survival in alternative environments. For example, flagella are also required for swimming and swarming,48 extracellular polymeric substances play a role in resistance and tolerance to dehydration,49 ribosomal proteins play an integral role in translation,44 respiratory enzymes are integral to electron transport,44 and quorum sensing systems play roles in a diverse array of functions from pathogenicity to sporulation.50 Among hypotheses to explain the increased resistance to antibiotics, Mah and O’Toole5 proposed a specific physiology of biofilm cells, supported later by the discovery of ndvB involved in the synthesis of cytoplasmic glucans by P. aeruginosa.7 Yet the existence of biofilm specific master regulators or even specific genes was not supported by a review of the biofilm literature.43,51 A recent collective analysis of transcriptomic results supports the idea of unique patterns of expression of genes that also play roles during growth or survival in environments other than a biofilm.44 It is possible that biofilm-specific genes are expressed in a small sub-population of the biofilm, such as persistor cells.8 The discovery of such genes or their proteins by global approaches would generally be obscured due to sample homogenization for transcriptomic and proteomic analyses.

Conclusions In conclusion, B. cereus ATCC14579 cultured in batch in the presence of an attachment surface grows to occur as two distinct populations, one attached to the surface and the other free-floating. The analysis presented offers proof that B. cereus growing as a biofilm is physiologically distinct from planktonic cells in exponential, transient, and stationary phase. The specificity of the biofilm proteome is not the result of a mere mixture of planktonic cells at various stages of growth. This analysis was based on an unbiased approach of principal component analysis, comparing the variations of the 823 protein spots. The biofilm-specific phenotype is due more to an altered profile of relative quantities than to the appearance or disappearance of unique protein spots. While this supports the hypothesis that biofilms of Gram positive bacteria have a unique pattern of gene expression, it does not point to the existence of biofilm-specific genes. Moreover, the data points to the existence of a new biofilm and surface influenced planktonic (BSP) population which is distinct to both planktonic and biofilm cells.

Acknowledgment. We thank Dr. Philip Hardwidge for critical reading of the manuscript and Dr. Karl Glover for use of his scanning densitometer. This work was supported by the South Dakota Agricultural Experiment Station (Journal series publication 3535), National Science Foundation/EPSCoR Grant No. EPS-0091948 and by the State of South Dakota. References (1) Kolter, R. Trends Microbiol. 2005, 13, 1-2. (2) Costerton, J. W.; Lewandowski, Z.; Caldwell, D. F.; Korber, D. E.; Lappin-Scott, H. M. Annu. Rev. Microbiol. 1995, 49, 711-745. (3) Watnick, P.; Kolter, R. J. Bacteriol. 2000, 182, 2675-2679. (4) Fux, C. A.; Costerton, J. W.; Stewart, P. S.; Stoodley, P. Trends Microbiol. 2005, 13, 34-40. (5) Mah, T. F.; O’Toole, G. A. Trends Microbiol. 2001, 9, 34-39. (6) Davies, D. Nat. Rev. Drug Discov. 2003, 2, 114-122. (7) Mah, T. F.; Pitts, B.; Pellock, B.; Walker, G. C.; Stewart, P. S.; O’Toole, G. A. Nature (London) 2003, 426, 306-310. (8) Lewis, K. Biochemistry (Mosc). 2005, 70, 267-274.

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