Bordetella pertussis (B. pertussis) is the causative agent of whooping cough, which is a highly contagious disease in the human respiratory tract. Despite vaccination since the 1950s, pertussis remains the most prevalent vaccine-preventable disease in developed countries. A recent resurgence pertussis is associated with the expansion of B. pertussis strains with a novel allele for the pertussis toxin (ptx) promoter ptxP3 in place of resident ptxP1 strains. The recent expansion of ptxP3 strains suggests that these strains carry mutations that have increased their fitness. Compared to the ptxP1 strains, ptxP3 strains produce more Ptx, which results in increased virulence and immune suppression. In this study, we investigated the contribution of gene expression changes of various genes on the increased fitness of the ptxP3 strains. Using genome-wide gene expression profiling, we show that several virulence genes had higher expression levels in the ptxP3 strains compared to the ptxP1 strains. We provide the first evidence that wildtype ptxP3 strains are better colonizers in an intranasal mouse infection model. This study shows that the ptxP3 mutation and the genetic background of ptxP3 strains affect fitness by contributing to the ability to colonize in a mouse infection model. These results show that the genetic background of ptxP3 strains with a higher expression of virulence genes contribute to increased fitness.
Citation: King AJ, van der Lee S, Mohangoo A, van Gent M, van der Ark A, et al. (2013) Genome-Wide Gene Expression Analysis of Bordetella pertussis Isolates Associated with a Resurgence in Pertussis: Elucidation of Factors Involved in the Increased Fitness of Epidemic Strains. PLoS ONE 8(6): e66150. doi:10.1371/journal.pone.0066150
Editor: Daniela Flavia Hozbor, Universidad Nacional de La Plata., Argentina
Received: January 7, 2013; Accepted: May 1, 2013; Published: June 11, 2013
Copyright: © 2013 King et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This project was supported by the RIVM (SOR project). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Bordetella pertussis is a human-specific pathogen and the causative agent of whooping cough, or pertussis, which is an acute respiratory disease that is particularly severe in infants. Universal immunization programs have contributed to a significant reduction in the incidence of serious disease and mortality caused by B. pertussis , especially in infants and children. However, pertussis remains one of the leading causes of vaccine-preventable deaths worldwide despite extensive immunization , . A resurgence in pertussis in recent years has been observed in highly immunized populations. Several causes for the re-emergence of pertussis have been suggested, including waning immunity and pathogen adaptation ,  , . Polymorphisms in B. pertussis surface proteins have been detected in several countries. Variations in the B. pertussis proteins pertussis toxin (Ptx) and pertactin (Prn) have been shown to affect vaccine efficacy in a mouse model  ,  , . Since the 1990s, strains with a novel allele for the Ptx promoter (ptxP3) associated with recent epidemics in the Netherlands have emerged in several European countries, replacing resident ptxP1 strains , . In the last 20 years, ptxP1 and ptxP3 have been predominating in the Dutch B. pertussis population. The recent expansion of ptxP3 strains in the Netherlands and other countries in Europe, Asia and North and South America suggests that ptxP3 strains carry mutations that have increased their fitness. Laboratory data has shown an increase in Ptx production in ptxP3 strains, and epidemiological data has suggested that the ptxP3 strains are more virulent   than the ptxP1 strains.
The expression of B. pertussis virulence factors is controlled by the two-component BvgAS sensory transduction system , , . BvgAS controls the expression of a spectrum of phenotypic phases transitioning between a virulent (Bvg+) phase and a nonvirulent (Bvg-) phase, which is referred to as phenotypic modulation –. During the virulent Bvg+ phase, the BvgAS system controls the expression of over 100 virulence genes  by binding phosphorylated BvgA to the promoters of the virulence genes. Many of these genes are part of the core regulon defined by Cummings et al. . The virulence core regulon consists of a set of 56 genes that are strongly upregulated in several different B. pertussis strains under virulent growth conditions. These genes include pertactin, pertussis toxin, filamentous hemagglutinin (FHA), fimbriae, adenlyate cyclase toxin, dermonecrotic toxin and the type III secretion system (TTSS) , . Differences in Bvg-regulated gene expression between Bordetella species prompted the examination of differential regulation among isolates of the same species. Differential gene expression patterns within a species may reflect ongoing microevolution and could lead to better insight into the mechanisms of host adaptation. Diversification of gene expression profiles may also influence pathogenicity, which has been suggested in Mycobacterium tuberculosis .
A recent microarray-based analysis of the gene content of over 170 B. pertussis clinical strains isolated in different countries revealed genomic differences between the strains. Genes present in all of the isolates (core genes) are assumed to be phylogenetically conserved, while the genes that are variably present (variable genes) are proposed to be horizontally acquired or differentially lost within the species. The core and variable genome has been defined for B. pertussis based on microarray studies , , . A strong correlation was found between the ptxP type and the gene content, suggesting that strains with different ptxP types form different lineages . A similar analysis previously revealed that the ptxP1 and ptxP3 lineages are distinguished by a region of 18 genes present in ptxP1 strains, but absent in all of the ptxP3 strains that have been analyzed to date . More recently, several sequencing and single nucleotide polymorphisms (SNP)-based studies have confirmed that ptxP3 isolates are grouped together and form a separate branch ,  . To our knowledge, it is not known how the B. pertussis ptxP3 strains differ in other key biological properties from the ptxP1 strains, but it is suggested that the ptxP3 strains are the fitter variants of B. pertussis , , .
While variation in genetic content is likely to be relevant in pathogenesis, differential gene expression may also be important. Gene expression profiling using DNA microarray technology provides a fingerprint of the full transcriptome, which allows a detailed comparison of strain-specific differences. In this study, we used genome-wide gene expression profiling, allelic exchange and a murine model of infection to gain insight into the factors involved in the global spread of the ptxP3 strains.
Growth and Strains
In a previous study, we analyzed the gene content of B. pertussis strains from different countries isolated between 1949 and 2008 using microarray-based CGH and found a strong correlation between the gene content and the ptxP allele . In this study, we analyzed the genome-wide microarray-based gene expression of a subset of these strains to evaluate the differences in expression between the B. pertussis strains isolated in the Netherlands between 1949 and 2008 carrying a ptxP1 (n = 9) or ptxP3 allele (n = 5). Strains were grown under Bvg+ conditions in a chemically defined growth medium ,  that provides highly reproducible gene expression and bacterial growth results . Triplicate shake flask cultivations (independent cultures) were grown for each strain. The strains were monitored spectrophotometrically at an optical density of 590 nm (OD590) to confirm logarithmic growth (data not shown). Changes in growth phase-associated gene expression were previously studied using transcriptional profiling of vaccine strain 509 under similar conditions . Based on these and other unpublished data (personal communication King et al.), the optimal harvest point for the RNA samples was estimated at OD = 0.4+/−0.05. This time point was chosen to minimize the specific effects of the growth phase.
Transcriptomic Analysis of B. pertussis Strains
Microarray-based gene expression was measured using the previously described pan-Bordetella microarray based on the sequence of B. pertussis (Tohama I strain) and all of the extra genes found in B. parapertussis strain 12822 and B. bronchiseptica strain RB50 . Genome-wide transcriptional profiles of the B. pertussis strains carrying the ptxP1 allele (n = 9) and ptxP3 allele (n = 5) were determined to identify differentially regulated genes. The transcript levels were assessed in all (at least) -three biological replicates of each strain (Table S1). Microarray data of the 3714 genes present in all of the strains analyzed in this study were used. Data analysis revealed significant differential gene expression in 975 genes between both groups of strains (ptxP1 and ptxP3; false discovery rate (FDR) <0.05; corresponds to P<0.013117). The transcription of 952 genes was significantly upregulated in ptxP3 strains, with 818 core genes. For 134 variable genes, expression was significantly higher in the ptxP3 strains. The transcription of 23 genes was significantly downregulated in the ptxP3 strains, with 19 core genes (Table 1). Four variable genes were downregulated in the ptxP3 strains. A summary of all of the significantly regulated genes is provided in Table S2.
The proportion of various functional categories of the differentially expressed genes in the ptxP3 and the ptxP1 strains were determined. The functional categories classified by Parkhill et al.  were used with modification in genes involved in pathogenicity . Differentially expressed genes were detected in several functional categories. There were 125 conserved hypothetical genes differentially expressed in ptxP3 compared to ptxP1, followed by cell surface genes, regulation genes, miscellaneous genes and pseudogenes (Figure 1). Differences in expression relative to the total number of genes present in the strains in the amino acid biosynthesis, energy metabolism, regulation and central/intermediary metabolism categories were significantly increased (P<0.05) in all of the genes differentially expressed between ptxP3 and ptxP1 (Figure 1).
The gene count (absolute number of genes) of differentially expressed genes per category (blue). And the gene count of differentially expressed genes relative to the total number of genes (red) present in the genomes of the analyzed strains.
Several virulence-associated genes were differentially expressed in the ptxP3 strains. Of the 57 genes belonging to the virulence core regulon, which is described as the genes expressed in all B. pertussis strains when grown under conditions that promote virulence (genes implicated in B. pertussis virulence) , , , about 21 (37%) (Table 2) had a significantly higher abundance of transcripts in the B. pertussis strains carrying the ptxP3 allele, suggesting that the ptxP3 strains may be more virulent. The differences in expression between the ptxP1 and ptxP3 strains were significant even though they generally did not differ by more than a factor of 1.5-fold, with the exception of the, BP0500, BP1568, BP2252, BP2254 and BP2315 (Table 2). Interestingly, the virulence sensor protein (BvgS) that forms the BvgAS two component sensory regulatory system important in the regulation of Bordetella virulence was slightly, but significantly, upregulated in the ptxP3 strains. The virulence factor transcriptional regulator (BvgA) also showed a slightly higher expression (P = 0.014172) in the ptxP3 strains, but the difference was slightly above the FDR <0.05 cutoff. The microarray data showed a slightly higher (factor of 1.14–1.25-fold) expression of the genes in the ptx-operon. BP3783 (ptxA), BP3784 (ptxB), BP3785 (ptxD), BP3786 (ptxE) and BP3787 (ptxC), the difference in expression of ptxB in ptxP3 and ptxP1 strains with a 1.14 fold change P = 0.022 FDR = 0.07, slightly above the FDR cutoff of 0.05 and is there was not shown in Table 2. BP1119, the serotype 2 precursor was expressed significantly lower in ptxP3 strains (not shown).
Microarray data were validated by real time quantitative PCR assays on a small selection, 5 (BVG controlled) genes (Table 3). Real time quantitative PCR analysis of this set was highly concordant with the microarray gene expression data r2 = 0.88 Figure 2.
Log-transformed (in base 10) fold change values of the Q-PCR data (y-axis) were plotted against the log-transformed fold change values of microarray data (x-axis). The coefficient of determination (R 2) is given.
Colonization of ptxP1 and ptxP3 B. Pertussis Strains in a Mouse Model
To discriminate between the role of individual ptxP3 and ptxP1 mutations and the genetic background (gb) of the strains, we constructed two different isogenic strains that carry the ptxP3 allele in the ptxP1 genetic background (P1 gb:ptxP3) or the ptxP1 allele in the ptxP3 genetic background (P3 gb:ptxP1). The colonization of isogenic and wild type strains was tested in an intranasal mouse model that was previously described  . Colonization was assessed four days after infection in the lungs and trachea of mice (Fig. 2). We demonstrate for the first time that wild type ptxP3 strains colonize more efficiently than the wild type ptxP1 strains in the lungs and trachea of mice (P<0.0001). The P3 gb:ptxP1 strains and wild type ptxP3 strains showed similar colonization levels in the lungs and trachea, suggesting that the genetic background of the strain significantly contributes to the observed differences. The P1 gb:ptxP3 strains showed increased colonization in the lungs and trachea than the wild type ptxP1 strains (P<0.0001), which suggests that the ptxP3 allele contributes to the increased colonization. Colonization was decreased in the P1 gb:ptxP3 strains compared to the wild type ptxP3 strains, but the differences were not significantly different in lungs and trachea (Fig. 3). In conclusion, these results suggest that the ptxP3 allele and the genetic background in which this allele is embedded enhance colonization in a mouse model.
Mice were intranasally infected with the wildtype ptxP1 strain, the ptxP3 strain, isogenic strains carrying the ptxP3 allele in the ptxP1 genetic background (P1 gb:ptxP3) or the ptxP1 allele in the ptxP3 genetic background (P3 gb:ptxP1). CFUs were determined in the trachea and lungs four days post-infection. The mean is indicated by a thin line. P-values (uncorrected for multiple tests) were shown if greater than 0.05. The experiment was performed two times representative result is shown.
Microarray analysis was used to evaluate differences in gene expression on a genome-wide scale between two different B. pertussis lineages. A previous study demonstrated that B. pertussis strains carrying the ptxP3 allele differ from strains with the ptxP1 allele in the ptxP promoter sequence and gene content based on microarray-based CGH analyses . PtxP3 strains have been associated with pertussis epidemics in several countries worldwide  , , and evidence has suggested that the ptxP3 strains are more virulent . Mooi et al.  showed that ptxP3 strains produce a higher level of pertussis toxin compared to strains with the ptxP1 allele, which may influence the fitness of these strains. In this study, we investigated differences between the ptxP1 and ptxP3 strains that could explain the success of the ptxP3 strains. We compared the transcriptional profiles of B. pertussis strains with the ptxP1 and ptxP3 alleles on a genome-wide scale. Gene expression analysis revealed that many genes, including genes that are known to be involved in virulence (most notably the BvgS gene), were more highly expressed in the ptxP3 strains. Previous studies have suggested that strains with different ptxP types form different lineages  –. This study provides the first evidence that a wildtype B. pertussis strain with the ptxP3 allele is a better colonizer in the intranasal mouse infection model than a B. pertussis strain with a ptxP1 allele (Fig. 2). By using allelic exchange and subsequent analysis in the intranasal mouse infection model, we showed that not only the ptxP3 allele is responsible for improved colonization and that the genetic background of B. pertussis strains also contributes to the success of the strain (Fig. 2).
Transcriptomic analysis and analysis of isogenic strains in a mouse model were used to gain insight into the biological properties of B. pertussis strains with different ptxP alleles, particularly ptxP1 and ptxP3. Using transcriptomics, we attempted to identify new polymorphic loci important for adaptation and virulence. Because ptxP3 strains are more successful  ,  and possibly more virulent , we hypothesized that loci enhancing the virulence are more highly expressed in these strains. In a previous study by Mooi et al. , several arguments were raised that underlined the role of the ptxP3 mutation in the success of these strains. We investigated whether various genes expressed at higher levels in ptxP3 strains may contribute to the increased fitness of the ptxP3 strains. The whole genome-level gene expression profiles of B. pertussis strains with either the ptxP1 or ptxP3 alleles revealed loci in the B. pertussis population that are differentially expressed between the strains with ptxP1 and ptxP3 alleles. The transcriptional profiles demonstrate that many genes (n = 952) are upregulated (FDR<0.05 and P<0.013117) in the ptxP3 strains. Q-PCR data for a small selection of genes confirmed the higher expression in ptxP3 strains compared to ptxP1 strains, although in two genes the higher expression in ptxP3 strains by Q-PCR was not significantly different. The correlation between results by Q-PCR and hybridization with the microarray were shown to be very good for the 5 genes selected. Differentially expressed genes involved in amino acid biosynthesis (P = 0.00005), energy metabolism (P = 0.00049), and regulation (P = 0.00786) between the ptxP1 and ptxP3 strains were significantly overrepresented. Cummings et al.  described a set of genes that form the virulence core regulon. The genes in this regulon encode factors that are required for efficient infection and transmission . Transcriptomic analyses of the ptxP1 and ptxP3 strains showed a 37% increase in expression of the virulence-associated genes that form the core regulon in the ptxP3 strains, which indicates that these strains may be more virulent. Of the 21 genes with increased expression in the ptxP3 strains, BP0500 (BteA alias bopC), BP1568 (serotype 3 precursor), BP2252, (bop B), BP2254 (bcrH 1) and BP2315 (vag 8) had expression levels that were more than 1.5-fold higher in the ptxP3 strains. The virulence sensor protein (BvgS) was also slightly, but significantly, upregulated in the ptxP3 strains. Han et al.  recently showed increased expression of BteA, which is thought to play a pivotal role in T3SS-mediated cell death – in non-vaccine type strains. BteA is known to be regulated by the BvgAS system. Our analysis showed increased expression of BteA in the B. pertussis strains carrying the ptxP3 allele. Significantly increased expression of the ptxP operon was detected by microarray based gene expression even though the difference was less than 1.5-fold (Table 2). Our Q-PCR data showed slightly higher expression of two subunits of Ptx however in contrary to the microarray data this difference was not significant (Table 3). Previously Mooi et al.  had shown by using an ELISA technique that PtxS1 was expressed significantly higher in ptxP3 strains compared to ptxP1 strains. Ptx has been suggested to increase the severity of B. pertussis infections because the related B. parapertussis, which does not express Ptx, causes a less severe infection . In summary, transcriptomic analyses revealed increased expression of several virulence-associated genes. The increased expression of these genes is likely to influence the virulence potential of the ptxP3 strains. The expression of BP1119, the serotype 2 precursor is significantly lower in ptxP3 strains.
The biological properties of wild type ptxP1 and ptxP3 strains were evaluated in vivo using an intranasal mouse infection model to determine the colonization ability of both strains in the trachea and lungs of mice (Fig. 2). We demonstrate for the first time significantly higher colonization of the wildtype ptxP3 strain (P<0.0001) in the trachea and lungs of mice compared to the wild type ptxP1 strain. Multivariate analyses performed by van Gent et al. previously showed that ptxP contributed to differences in colonization . Because ptxP1 and ptxP3 strains form separate lineages as shown by differences in genetic content and DNA sequencing and SNP studies  ,  , the contribution of genetic background was investigated in this study. To discriminate between the role of ptxP3 and ptxP1 mutations individually and the genetic background (gb) of the strains, two different isogenic strains were constructed carrying the ptxP3 allele in the ptxP1 genetic background (P1 gb:ptxP3) or the ptxP1 allele in the ptxP3 genetic background (P3 gb:ptxP1). In the mouse model, the strain with the ptxP3 genetic background, but not the ptxP3 allele itself (P3 gb: ptxP1), had a similar colonization ability as the wildtype ptxP3 strain. A significantly higher colonizing ability compared to wildtype ptxP1 strains was observed, suggesting that the genetic background of the ptxP3 strains plays a role in increasing the ability to colonize. Since the colonization ability was similar to the wildtype ptxP3 strain this result may also be interpreted in that the ptxP3 allele itself does not contribute that much to the higher colonizing ablility.In contrast, colonization with the strain with the ptxP3 allele in the genetic background of a ptxP1 strain (P1 gb: ptxP3) showed significantly increased colonization compared to the wildtype ptxP1 strain, which indicates that the ptxP3 allele itself also contributes to increased colonization in the mouse model. To our knowledge, no data on the effects of the genetic background of ptxP3 strains on colonizing ability have been previously published.
The higher colonization of ptxP3 strains in the lungs and trachea of mice is in agreement with epidemiological data. Mooi et al.  suggested that expansion of the ptxP3 strains in many countries worldwide indicates that ptxP3 increases the fitness of the strain or is linked to other genetic loci that do. These researchers suggest that the ptxP3 mutation confers increased fitness. A study in Sweden also suggested that B. pertussis strains differ in virulence because patients infected with strains of the PFGE profile BPSR11 were hospitalized for longer periods of time . The results of the present study support earlier indications of increased fitness in ptxP3 strains. We demonstrate that the ptxP3 allele and the genetic background of the strains contribute to increased fitness.
Materials and Methods
Bacterial Strains and Seedlot Preparation
The Bordetella pertussis strains used in this study are listed in Table 4. To improve the reproducibility of growth and gene expression, frozen working seedlots were prepared in a chemically defined medium with a standardized protocol. The starting materials were vials containing 1 ml Verwey medium (RIVM, Bilthoven, Netherlands; chemically undefined) with 20% glycerol and varying OD590 stored at −80°C. One vial of each strain was used to inoculate a primary 500 ml shake flask containing 200 ml THIJS medium ,  consisting of basic medium and a supplement (1% v/v) that was added to the basic medium shortly before inoculation. Shake flasks were incubated at 35°C on an orbital shaker at 200 RPM. When an OD590 of 1.0±0.2 was reached, a secondary shake flask was inoculated with 10 ml of the culture at OD590 = 1.0. For shake flasks at other optical densities, the volumes were adjusted to ensure that an equal amount of cells were used to inoculate each secondary shake flask. Secondary shake flasks were incubated at 35°C and 200 RPM until an OD of 1.00±0.05 was reached. The cultures were mixed with glycerol (17% v/v), divided into 10 ml working seedlots and stored at −140°C.
For each strain, a preculture was inoculated with 10 ml of the seedlot. Precultures were grown in 500 ml shake flasks containing 200 ml THIJS medium at 35°C on an orbital shaker at 200 RPM. When the preculture reached OD590 = 1.00±0.05, 3 secondary shake flasks were started for each strain. The triplicate cultivations were inoculated with 10 ml preculture and grown as described. The initial density was OD590 = 0.050±0.05 for all of the secondary cultivations. Separate samples were collected from each secondary shake flask for RNA isolation and consecutive microarray analysis when the OD590 was 0.4±0.05.
RNA Isolation, Preparation of Labeled cDNA and Microarray Analysis
For fixation of the RNA expression profile, 1 volume of bacterial culture was mixed with 2 volumes of a RNase retarding solution –. For each microarray sample, 2.5 ml of the culture at OD590 = 1.0 was used. For samples at other optical densities, the volumes were adjusted such that an equal amount of cells was used for each sample. The samples were concentrated by centrifugation and treated with Tris-EDTA buffer containing 0.5 mg/ml lysozymes (Sigma-Aldrich, Zwijndrecht, The Netherlands) for 3 minutes. Total RNA was extracted with the SV Total RNA Isolation System (Promega Benelux, Leiden, The Netherlands) according to the manufacturer’s protocol. The nucleic acid concentration was adjusted by precipitation, and spectral analysis was used to determine the final nucleic acid concentration and purity. RNA integrity was confirmed with the Bioanalyzer RNA6000 Nano assay (Agilent Technologies, Amstelveen, The Netherlands) according to the manufacturer's protocol.
Custom pan-Bordetella microarrays were constructed using the 8 x 15K format developed by Agilent Technologies (Wilmington, Delaware, USA). The set of 5,910 60-mer oligonucleotides (60-mer) in which one oligonucleotide corresponds to one gene covered 94% of the genes in the three sequenced Bordetella strains, including B. pertussis Tohama I, B. parapertussis 12822 and B. bronchiseptica RB50. In addition, 98 control probes were included in the microarray, and all of the spots were printed in duplicate (non adjacent). User-defined probes were uploaded through the Agilent eArray Web portal (http://earray.chem.agilent.com/earray/). Additional details on microarray production are available through the ArrayExpress microarray data repository (accession number A-MEXP-1697).
A two-color hybridization format was used for microarray analysis. For each biological replicate, RNA extracted from each test strain was used to create Cy5-labeled cDNA, and the (common) reference sample containing equal amounts of RNA from all experimental samples was used to create Cy3-labeled cDNA. The use of a common reference across different cDNA microarray experiments improves the reproducibility of the hybridization signals and allows the gene expression levels from separate experiments to be compared. Total RNA samples were reverse transcribed to cDNA and labeled with Cy3/Cy5 dyes using the Chipshot Indirect Labeling kit (Promega Benelux) according to the manufacturer’s protocol with one modification. A total of 2 µl of random nonamer primer without oligo-dT primers was used per reaction to reverse transcribe the total RNA. For each hybridization, 300 ng Cy3-labeled cDNA and 300 ng Cy5-labeled cDNA were combined with 5 µl 10× blocking agent and 1 µl 25× fragmentation buffer in a total volume of 25 µl according to the manufacturer’s protocol (Agilent). Prior to loading on the microarray, the hybridization solution was heated for 3 minutes at 60°C. Microarray slides were hybridized and treated as described in the Agilent protocols for two-color microarray-based gene expression analysis. Microarray experiment details are also deposited at array express under accession number E-MTAB-1594.
For quantitative PCR the total RNA was treated with DNase I to remove contaminating DNA. The quality of the RNA was evaluated by Agilent Bioanalyzer and Naonodrop spectrophotometry. The RNA was reverse transcribed using random hexamers and oligo d(T). Samples were tested in 384 well format in duplicate with a no-RT control for each sample. Universal Human Reference RNA and the control sample were also tested in duplicate with a no-RT control. The samples were analyzed with 6 assays: 5 target assays and 1 endogenous control, as detailed below. All samples were amplified using the Applied Biosystems Prism® 7900 Sequence Detection System with standard cycling conditions. Primer sequences for the examined 6 genes are in Table S3. Samples were tested in duplicate. BP0015 was used as endogenous control. All relative quantification data were calculated using the delta delta CT method. The gene expression for ptxP1 strains was calculated as mean +/− SD for 8 strains and the gene expression for ptxP3 strains was calculated as mean +/− SD for 5 strains. The relative difference in expression were presented as the ratio of ptxP3 strains to ptxP1 strains.
Microarray Data Mining
The hybridized slides were scanned at a 5 µm resolution using a ScanArray Gx plus microarray scanner (Perkin Elmer) equipped with ScanArrray express software. The images from Agilent pan-Bordetella microarrays were analyzed using ImaGene software (Biodiscovery, El Segundo, CA, USA). Individual arrays were internally normalized between the Cy3 and Cy5 channels by LOWESS normalization. A hybridization ratio logarithm [log2(Cy5/Cy3)] was calculated and the gene expression data were normalized to the expression of a BP0015 DNA-directed RNA polymerase beta chain in each microarray slide to compensate for variations between the slides. The normalized data were further processed using Microsoft Excel and TMEV software from the TM4 suite (TIGR). Biological replicates were analyzed separately for all of the strains. The average expression of each individual gene was calculated for all of the strains carrying the ptxP1 and ptxP3 alleles. P-values were calculated with one–way ANOVA statistical analysis (t-test). The fold change in the ptxP3 and ptxP1 strains was determined as follows: 2 ∧ (average of expression in ptxP3 strains – average of expression in ptxP1 strains), if this number, between the brackets, is greater then 0 if not then 1/2 ∧ (average of expression in ptxP3 strains – average of expression in ptxP1 strains. All microarray data have been deposited in Array express under accession number E-TAB-1594.
Construction of Recombinant B. Pertussis Strains
To generate a B. pertussis strain with the ptxP1 allele in the genetic background of the ptxP3 strain (P3gb, ptxP1), we constructed a suicide vector pSS1129– ptxP1 by PCR amplification of an internal fragment of the ptxP promoter from genomic strain B0213 (Tohama I) using the Xba1F (GCT CTA GAC GCT GCA GTC CAA GGC GGT CGT C) and EcoR1R (GGA ATT CAT CCC GTC TTC CCC TCT GCG TTT TGA TG) primers. The PCR product was cloned into pSS1129 using the Xba1 and EcoR1 restriction sites. Suicide vectors were introduced into B. pertussis (B1917, ptxP3) via conjugation using E. coli SM10 as a donor strain. B. pertussis mutants were selected based on growth on BG-agar containing appropriate antibiotics. Removal of the vector sequences was forced by growing the conjugates on BG agar plates with 300 µg/ml streptomycin. A B. pertussis strain with a ptxP3 allele was constructed in the genetic background of a ptxP1 strain (P1gb, ptxP3) in a similar manner. The suicide vector pSS1129-ptxP3 was constructed and introduced in B. pertussis (B0602, ptxP1). Proper insertion was confirmed by sequencing. The gene content of all of the mutant B. pertussis strains was analyzed using microarray-based CGH analysis. The strains B1917, ptxP3 and B0602, ptxP1 have the most common gene content type for ptxP3 and ptxP1 strain respectively and were therefore good respresentatives for these two groups.
Mouse Infection Model
All animal experiments were conducted according to relevant national and international guidelines. Strains were grown on Bordet-Gengou plates and animal experiments were performed as previously described . This study was agreed upon by the Committee on animal Experimentation of the Netherlands Vaccine Institute (DEC-NVI, Bilthoven, the Netherlands) under permit numbers 201000079 and 201000257. Animal handling in this study was carried out in accordance with relevant Dutch national legislation, including the 1997 Dutch Act on Animal Experimentation.
Microarray gene expression data for all strains analyzed in this study. DNA microarray analysis was used to measure the mRNA levels in ptxP3 strains compared to mRNA levels in ptxP1 strains. Gene expression data were shown for all replicates for each individual strain (ptxP1 strains with a green column head and ptxP3 strains with red column head). The gene expression data were normalized to the expression of a BP0015 DNA-directed RNA polymerase beta chain in each microarray slide to compensate for variations between the slides. The average expression of each individual gene was calculated for all of the strains carrying the ptxP1 and ptxP3 alleles. P-values were calculated with one–way ANOVA statistical analysis (t-test), P-values lower than 0.05 were highlighted in green. The fold change in the ptxP3 and ptxP1 strains were calculated as described in materials and methods section. The false discovery rate (FDR) is shown.
Summary of all genes significantly up or down regulated in strains carrying the ptxP3 allele compared to strains with the ptxP1 allele. The gene ID, gene name and gene category are shown.
Quantitative PCR Primer sequences for genes by Q-PCR in this study. Primer sequences for 6 assays: 5 target assays and 1 endogenous control are shown. The gene IDs for targeted genes are given in the first column.
The authors thank Frits Mooi for constructive discussions and Jeroen Pennings for assistance with microarray data mining.
Conceived and designed the experiments: AJK. Performed the experiments: SvdL AM MvG AvdA AJK. Analyzed the data: AJK SvdL BW. Wrote the paper: AJK BW.
- 1. Mattoo S, Cherry JD (2005) Molecular pathogenesis, epidemiology, and clinical manifestations of respiratory infections due to Bordetella pertussis and other Bordetella subspecies 1. ClinMicrobiolRev 18: 326–382. doi: 10.1128/cmr.18.2.326-382.2005
- 2. Crowcroft NS, Pebody RG (2006) Recent developments in pertussis. Lancet 367: 1926–1936. doi: 10.1016/s0140-6736(06)68848-x
- 3. He Q, Mertsola J (2008) Factors contributing to pertussis resurgence 10. FutureMicrobiol 3: 329–339. doi: 10.2217/174609188.8.131.529
- 4. de Melker HE, Schellekens JF, Neppelenbroek SE, Mooi FR, Rumke HC, et al. (2000) Reemergence of pertussis in the highly vaccinated population of the Netherlands: observations on surveillance data. EmergInfectDis 6: 348–357. doi: 10.3201/eid0604.000404
- 5. Guris D, Strebel PM, Bardenheier B, Brennan M, Tachdjian R, et al. (1999) Changing epidemiology of pertussis in the United States: increasing reported incidence among adolescents and adults, 1990–1996. ClinInfectDis 28: 1230–1237. doi: 10.1086/514776
- 6. Mooi FR, Van Loo IH, King AJ (2001) Adaptation of Bordetella pertussis to vaccination: a cause for its reemergence? EmergInfectDis 7: 526–528. doi: 10.3201/eid0707.017708
- 7. King AJ, Berbers G, van Oirschot HF, Hoogerhout P, Knipping K, et al. (2001) Role of the polymorphic region 1 of the Bordetella pertussis protein pertactin in immunity. Microbiology 147: 2885–2895.
- 8. Komatsu E, Yamaguchi F, Abe A, Weiss AA, Watanabe M (2010) Synergic effect of genotype changes in pertussis toxin and pertactin on adaptation to an acellular pertussis vaccine in the murine intranasal challenge model. Clin Vaccine Immunol 17: 807–812. doi: 10.1128/cvi.00449-09
- 9. Watanabe M, Komatsu E, Abe K, Iyama S, Sato T, et al. (2002) Efficacy of pertussis components in an acellular vaccine, as assessed in a murine model of respiratory infection and a murine intracerebral challenge model. Vaccine 20: 1429–1434. doi: 10.1016/s0264-410x(01)00460-1
- 10. Bottero D, Gaillard ME, Fingermann M, Weltman G, Fernandez J, et al. (2007) Pulsed-field gel electrophoresis, pertactin, pertussis toxin S1 subunit polymorphisms, and surfaceome analysis of vaccine and clinical Bordetella pertussis strains. Clin Vaccine Immunol 14: 1490–1498. doi: 10.1128/cvi.00177-07
- 11. Kallonen T, Grondahl-Yli-Hannuksela K, Elomaa A, Lutynska A, Fry NK, et al. (2011) Differences in the genomic content of Bordetella pertussis isolates before and after introduction of pertussis vaccines in four European countries. Infect Genet Evol 11: 2034–2042. doi: 10.1016/j.meegid.2011.09.012
- 12. Advani A, Gustafsson L, Ahren C, Mooi FR, Hallander HO (2011) Appearance of Fim3 and ptxP3-Bordetella pertussis strains, in two regions of Sweden with different vaccination programs. Vaccine 29: 3438–3442. doi: 10.1016/j.vaccine.2011.02.070
- 13. Mooi FR, Van Loo IH, van Gent M, He Q, Bart MJ, et al. (2009) Bordetella pertussis strains with increased toxin production associated with pertussis resurgence 2. EmergInfectDis 15: 1206–1213. doi: 10.3201/eid1508.081511
- 14. Advani A, Gustafsson L, Carlsson RM, Donnelly D, Hallander HO (2007) Clinical outcome of pertussis in Sweden: association with pulsed-field gel electrophoresis profiles and serotype 4. APMIS 115: 736–742. doi: 10.1111/j.1600-0463.2007.apm_628.x
- 15. Cummings CA, Bootsma HJ, Relman DA, Miller JF (2006) Species- and strain-specific control of a complex, flexible regulon by Bordetella BvgAS. JBacteriol 188: 1775–1785. doi: 10.1128/jb.188.5.1775-1785.2006
- 16. Shrivastava R, Miller JF (2009) Virulence factor secretion and translocation by Bordetella species. Curr Opin Microbiol 12: 88–93. doi: 10.1016/j.mib.2009.01.001
- 17. Coote JG (2001) Environmental sensing mechanisms in Bordetella. AdvMicrobPhysiol 44: 141–181. doi: 10.1016/s0065-2911(01)44013-6
- 18. Deora R (2002) Differential regulation of the Bordetella bipA gene: distinct roles for different BvgA binding sites. J Bacteriol 184: 6942–6951. doi: 10.1128/jb.184.24.6942-6951.2002
- 19. Deora R, Bootsma HJ, Miller JF, Cotter PA (2001) Diversity in the Bordetella virulence regulon: transcriptional control of a Bvg-intermediate phase gene. Mol Microbiol 40: 669–683. doi: 10.1046/j.1365-2958.2001.02415.x
- 20. Jones AM, Boucher PE, Williams CL, Stibitz S, Cotter PA (2005) Role of BvgA phosphorylation and DNA binding affinity in control of Bvg-mediated phenotypic phase transition in Bordetella pertussis. Mol Microbiol 58: 700–713. doi: 10.1111/j.1365-2958.2005.04875.x
- 21. Bootsma RJ, Craig CM (2002) Global and local contributions to the optical specification of time to contact: observer sensitivity to composite tau. Perception 31: 901–924. doi: 10.1068/p3230
- 22. Streefland M, van de Waterbeemd B, Happe H, van der Pol LA, Beuvery EC, et al. (2007) PAT for vaccines: the first stage of PAT implementation for development of a well-defined whole-cell vaccine against whooping cough disease. Vaccine 25: 2994–3000. doi: 10.1016/j.vaccine.2007.01.015
- 23. Gao Q, Kripke KE, Saldanha AJ, Yan W, Holmes S, et al. (2005) Gene expression diversity among Mycobacterium tuberculosis clinical isolates. Microbiology 151: 5–14. doi: 10.1099/mic.0.27539-0
- 24. King AJ, van Gorkom T, van der Heide HG, Advani A, van der Lee S (2010) Changes in the genomic content of circulating Bordetella pertussis strains isolated from the Netherlands, Sweden, Japan and Australia: adaptive evolution or drift? BMC Genomics 11: 64. doi: 10.1186/1471-2164-11-64
- 25. Heikkinen E, Kallonen T, Saarinen L, Sara R, King AJ, et al. (2007) Comparative Genomics of Bordetella pertussis Reveals Progressive Gene Loss in Finnish Strains. PLoSONE 2: e904. doi: 10.1371/journal.pone.0000904
- 26. King AJ, van Gorkom T, Pennings JL, van der Heide HG, He Q, et al. (2008) Comparative genomic profiling of Dutch clinical Bordetella pertussis isolates using DNA microarrays: identification of genes absent from epidemic strains 2. BMCGenomics 9: 311. doi: 10.1186/1471-2164-9-311
- 27. Bart MJ, van Gent M, van der Heide HG, Boekhorst J, Hermans P, et al. (2010) Comparative genomics of prevaccination and modern Bordetella pertussis strains. BMC Genomics 11: 627. doi: 10.1186/1471-2164-11-627
- 28. van Gent M, Bart MJ, van der Heide HG, Heuvelman KJ, Kallonen T, et al. (2011) SNP-based typing: a useful tool to study Bordetella pertussis populations. PLoS One 6: e20340. doi: 10.1371/journal.pone.0020340
- 29. Lam C, Octavia S, Bahrame Z, Sintchenko V, Gilbert GL, et al. (2012) Selection and emergence of pertussis toxin promoter ptxP3 allele in the evolution of Bordetella pertussis. Infect Genet Evol 12: 492–495. doi: 10.1016/j.meegid.2012.01.001
- 30. Thalen M, van den IJ, Jiskoot W, Zomer B, Roholl P, et al. (1999) Rational medium design for Bordetella pertussis: basic metabolism. J Biotechnol 75: 147–159. doi: 10.1016/s0168-1656(99)00155-8
- 31. Thalen M, Venema M, van den IJ, Berwald L, Beuvery C, et al. (2006) Effect of relevant culture parameters on Pertussis Toxin expression by Bordetella pertussis. Biologicals 34: 213–220. doi: 10.1016/j.biologicals.2005.11.002
- 32. van de Waterbeemd B, Streefland M, Pennings J, van der Pol L, Beuvery C, et al. (2009) Gene-expression-based quality scores indicate optimal harvest point in Bordetella pertussis cultivation for vaccine production. Biotechnol Bioeng 103: 900–908. doi: 10.1002/bit.22326
- 33. Parkhill J, Sebaihia M, Preston A, Murphy LD, Thomson N, et al. (2003) Comparative analysis of the genome sequences of Bordetella pertussis, Bordetella parapertussis and Bordetella bronchiseptica. NatGenet 35: 32–40. doi: 10.1038/ng1227
- 34. Herrou J, Debrie AS, Willery E, Renauld-Mongenie G, Locht C, et al. (2009) Molecular evolution of the two-component system BvgAS involved in virulence regulation in Bordetella. PLoS One 4: e6996. doi: 10.1371/journal.pone.0006996
- 35. Mooi FR (2010) Bordetella pertussis and vaccination: the persistence of a genetically monomorphic pathogen. Infect Genet Evol 10: 36–49. doi: 10.1016/j.meegid.2009.10.007
- 36. Octavia S, Sintchenko V, Gilbert GL, Lawrence A, Keil AD, et al. (2012) Newly emerging clones of Bordetella pertussis carrying prn2 and ptxP3 alleles implicated in Australian pertussis epidemic in 2008–2010. J Infect Dis 205: 1220–1224. doi: 10.1093/infdis/jis178
- 37. Kallonen T, He Q (2009) Bordetella pertussis strain variation and evolution postvaccination 1. ExpertRevVaccines 8: 863–875. doi: 10.1586/erv.09.46
- 38. Mooi FR, van Loo IH, van Gent M, He Q, Bart MJ, et al. (2009) Bordetella pertussis strains with increased toxin production associated with pertussis resurgence. Emerg Infect Dis 15: 1206–1213. doi: 10.3201/eid1508.081511
- 39. Han HJ, Kuwae A, Abe A, Arakawa Y, Kamachi K (2011) Differential expression of type III effector BteA protein due to IS481 insertion in Bordetella pertussis. PLoS One 6: e17797. doi: 10.1371/journal.pone.0017797
- 40. Panina EM, Mattoo S, Griffith N, Kozak NA, Yuk MH, et al. (2005) A genome-wide screen identifies a Bordetella type III secretion effector and candidate effectors in other species. Mol Microbiol 58: 267–279. doi: 10.1111/j.1365-2958.2005.04823.x
- 41. Kuwae A, Matsuzawa T, Ishikawa N, Abe H, Nonaka T, et al. (2006) BopC is a novel type III effector secreted by Bordetella bronchiseptica and has a critical role in type III-dependent necrotic cell death. J Biol Chem 281: 6589–6600. doi: 10.1074/jbc.m512711200
- 42. French CT, Panina EM, Yeh SH, Griffith N, Arambula DG, et al. (2009) The Bordetella type III secretion system effector BteA contains a conserved N-terminal motif that guides bacterial virulence factors to lipid rafts. Cell Microbiol 11: 1735–1749. doi: 10.1111/j.1462-5822.2009.01361.x
- 43. Watanabe M, Nagai M (2004) Whooping cough due to Bordetella parapertussis: an unresolved problem. Expert Rev Anti Infect Ther 2: 447–454. doi: 10.1586/14787184.108.40.2067
- 44. van Gent M, van Loo IH, Heuvelman KJ, de Neeling AJ, Teunis P, et al. (2011) Studies on Prn variation in the mouse model and comparison with epidemiological data. PLoS One 6: e18014. doi: 10.1371/journal.pone.0018014
- 45. Medhekar B, Shrivastava R, Mattoo S, Gingery M, Miller JF (2009) Bordetella Bsp22 forms a filamentous type III secretion system tip complex and is immunoprotective in vitro and in vivo. Mol Microbiol 71: 492–504. doi: 10.1111/j.1365-2958.2008.06543.x
- 46. Mei J, Shen X, Zha J, Sun B, Shen M, et al. (2005) [Study on the molecular epidemiology of Mycobacterium tuberculosis in Shanghai]. Zhonghua Liu Xing Bing Xue Za Zhi 26: 707–710.
- 47. Li WM, Wang SM, Li CY, Liu YH, Shen GM, et al. (2005) Molecular epidemiology of Mycobacterium tuberculosis in China: a nationwide random survey in 2000. Int J Tuberc Lung Dis 9: 1314–1319.