P. aeruginosa Isolate and Collection Strategies

Overall, 501 P. aeruginosa isolates cultured from the environment (n=106), animal clinical specimens (n=106), and non-CF (n=129) and CF patients (n=160) in South East Queensland, Australia were examined (Table S1). Four-hundred and eighty-seven (97%) isolates were collected prospectively between February 2006 and February 2009, and 14 (13 non-CF, 1 animal) were cultured between 2002 and 2005. Their DNA was extracted, they were confirmed as P. aeruginosa by real-time polymerase chain reaction (PCR) assay as described previously [33], and then the isolates and their extracted DNA were stored at −80°C until further testing.

Riverine isolates were cultured from surface water grab samples and/or air-water interface swabs from three South East Queensland river systems, the Lower Brisbane, Logan and North Pine Rivers. Lower Brisbane River isolates were sampled from 49 collection sites at 1.5 km intervals extending from the river mouth to 72 kms upstream. This geographical region included industrial, urban, and rural habitats (Figure 1). Logan River isolates were sampled from 14 collection sites over 126 kms, while isolates from the North Pine River comprised 12 collection sites over 52 kms. Logan and North Pine River collection sites extended from the mouth to the headwaters and were associated with predominantly rural and urban habitats (Figures S1 and S2). All riverine samples were categorised in terms of the distance they were collected from the river mouth [i.e. at 5 km intervals], and site land use [i.e. industrial, urban, or rural] (Table S1).

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Figure 1

Map (1136,268) of the Lower Brisbane River showing land use categories.

One-hundred ml of each environmental water sample was passed initially through a 47mm, 0.45 micron cellulose filter. Filtered water and swab samples were cultured onto MPAC agar (BD BBL™, North Ryde, Australia) at 42°C for 24 to 48-hours. All suspect colonies and six random subcultures (for heavily contaminated cultures only) were inoculated onto MacConkey Agar No. 2 (Oxoid Australia Pty. Ltd., Adelaide, Australia). Presumptive P. aeruginosa isolates were screened by real-time PCR and, once confirmed, were genotyped using enterobacterial repetitive intergenic consensus (ERIC)-PCR typing assays [34].

In all, 33 (67%) of the 49 Lower Brisbane River collection sites grew P. aeruginosa resulting in 251 individual colonies [median (range) colonies/positive collection site (PCS)=4 (1–25)], and 61 different ERIC-PCR genotypes [median genotypes/PCS=1 (1–6)]. In addition, seven (27%) of 26 Logan and North Pine River sample collection sites were culture positive generating 223 individual colonies [median colonies/PCS=4 (1–67)] and six genotypes [median genotypes/PCS=1(1–1)]. One isolate from each ERIC-PCR genotype and all positive collection sites were selected for MLST [Lower Brisbane River (n=64), Logan River (n=5) and North Pine River (n=1)].

Other environmental P. aeruginosa isolates used in the study consisted of: (i) 25 isolates cultured from prospectively collected municipal pool (n=19), tap (n=5) and tank (n=1) water samples submitted to the Queensland Health Public Health Microbiology Laboratory for routine monitoring between September 2008 and January 2009; and (ii) 11 household sink isolates collected from nine non-CF households during a separate environmental investigation in 2007. Thus, the 106 environmental isolates submitted for MLST comprised 70 (66%) isolates cultured from three river systems, 25 (24%) from pool, tank and tap water specimens, and 11 (10%) derived from household sinks.

MLST was also performed on 106 P. aeruginosa isolates collected from various infection sites involving 10 domestic or native animal species (57 [54%] dogs, 24 [23%] horses, 11 [10%] cats, six possums [5.5%], three snakes [3%], and one each from a bird, cow, goat, koala, and a lizard [n=106 individual animals]) and submitted to IDEXX Laboratories Pty. Ltd. (East Brisbane) and The University of Queensland Veterinary Diagnostic Laboratory during 2005–2009.

MLST was performed on 129 non-CF human P. aeruginosa isolates collected from 129 individual adult and paediatric patients receiving healthcare in eight hospitals in South East Queensland and included a variety of healthcare-associated and community-acquired infections (38 (30%) respiratory, 20 (16%) urine, 19 (15%) superficial wound, 18 (14%) blood, 18 (14%) ear, 14 (11%) other sterile site, and 2 (1.5%) eye). Of the 38 non-CF respiratory isolates, 14 were from patients with bronchiectasis (n=13) and chronic obstructive pulmonary disease (n=1), and each were treated at the same hospital, including the same inpatient wards, as those attending the primary regional adult CF clinic.

The 160 CF isolates were collected from 145 sputum samples from 145 patients participating in a national multi-centre cross-sectional prevalence study [22]. All isolates were screened initially using ERIC-PCR genotyping assays. A representative range of abundant local and randomly assigned unique P. aeruginosa genotypes underwent MLST analysis. Strains selected for MLST were categorised into three groups depending on their overall prevalence within the Queensland CF patient population: (i) major or common CF strains [ST-649 (AUST-01), ST-775 (AUST-02) and ST-801 (AUST-06)] found in ≥10% of patients (n=35 isolates); (ii) 21 minor CF strains, including two ST-17 (Clone C) isolates, detected in clusters of 1–5% of patients (n=50 isolates); and (iii) 75 unique CF strains from individual patients, including a single LES isolate [22].

Multilocus Sequence Analysis

PCR amplification, bi-directional sequencing, and ST assignment was performed in accordance with the P. aeruginosa PubMLST website [27]. Evolutionary parameters, including the number of polymorphic nucleotide sites and amino acids, the ratio of nonsynonymous to synonymous amino acid substitutions (dN/dS ratio), and the G+C content of each locus were calculated using START2 version 0.9.0 beta software and the P. aeruginosa PubMLST website [27], [35], [36].

Methods of Analysis

The Genetic Structure of Environmental P. aeruginosa

For reasons outlined in the Methods, we defined the population structure and diversity of P. aeruginosa in the environment by analysing isolates from the Lower Brisbane River. An isolate from each ERIC-PCR genotype and all positive collection sites were genotyped by MLST resulting in 58 STs. A dataset of 251 concatenated housekeeping gene sequences was then constructed assuming that each ERIC-PCR type belonged to only one ST [34].

Diversity

Rarefaction analysis demonstrated the high proportion of unique STs within the Lower Brisbane River sample. Despite the large sample size the rarefaction curve for unique STs was not saturated (Figure 2). We grouped STs into OTUs containing closely-related STs separated by a pairwise distance of 0.008 (23/2874 nucleotides), which was the mean pairwise difference among the population. Figure 2 shows that fewer than 50 randomly selected isolates were required for this rarefaction curve to be saturated, indicating that the population genetic diversity had been covered extensively within our sample of 251 isolates.

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Figure 2

Rarefaction curves showing diversity by unique sequence type (ST) and Operational Taxonomical Unit (OTU).

OTUs contained closely related STs, which were separated by the mean pairwise distance of the population, 0.008 (23/2874 nucleotides).

Table 2 shows the number, diversity and richness indices, and PERMANOVA results for these 251 isolates originating from different distances and land use categories along the Lower Brisbane River. Thirty (68%) of the 44 culture positive samples contained only one genotype, while only eight STs were isolated from multiple sample collection sites (median=2, range: 2–4). These observations were supported by high measures of diversity (i.e. low Simpson’s and high Shannon’s indices) for most distance groups and land use categories. Similarly, PERMANOVA analysis revealed no significant difference between the genetic diversity of P. aeruginosa isolates from each distance or land use category. An exception was isolates collected from industrial sites, which showed greater levels of sample richness (the ratio of the number of STs to the number of isolates =0.53) than isolates detected at urban or rural sites. Importantly, 77% of these industrial isolates were sampled from a single, major sewerage outfall site resulting in six different STs; however, one ST (ST-252) was isolated on 8 occasions. Thus, even though the richness of the industrial isolates was higher, the diversity of the industrial isolates was lower (lower Shannon’s index with confidence intervals that did not overlap with urban or rural isolates).

Table 2

Genetic diversity and recombination amongst the 251 Pseudomonas aeruginosa isolates Shannon’s Index (95% CI) collected from the Lower Brisbane River.

Category	Grouping1	Number of isolates	Number of STs	Number ofOTUs2	Simpson’s Index(95% CI)	Shannon’s Index(95% CI)	Chao 1 richnessestimate (95% CI)	PERMANOVAPseudo-F value3	R/M4
Distance from river mouth	<25 km	73	17	5	0.16 (0.11–0.22)	2.2 (1.9–2.4)	44 (26–111)	2.34 (0.076)	1.9
	25–50 km	80	19	4	0.16 (0.11–0.21)	2.2 (2.0–2.5)	106 (45–313)		3.7
	>50 km	98	23	4	0.08 (0.05–0.1)	2.7 (2.6–2.9)	151 (63–431)		3
Land usage	Industrial	17	9	4	0.24 (0.04–0.45)	1.7 (1.1–2.2)	16 (9–51)	1.79 (0.132)	4
	Rural	98	23	4	0.08 (0.05–0.1)	2.8 (2.6–2.9)	26 (23–38)		8.5
	Urban	136	27	5	0.10 (0.08–0.12)	2.6 (2.5–2.8)	44 (31–91)		4
Total	N/A	251	53	7	0.04 (0.04–0.05)	3.4 (3.3–3.6)	72 (60–109)	N/A

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¹N/A, Not applicable.

²OTU, operational taxonomic unit containing groups of isolates that varied by a pairwise distance of <0.008.

³ P-values are presented in parentheses.

⁴R/M, ratio of recombination to mutation; the LDhat likelihood permutation test P values were all <0.001.

Comparison of P. aeruginosa Isolates from Different Ecological Settings

We also determined whether the genetic diversity of isolates collected from CF patients was different from that observed in other local ecological settings (i.e. the natural environment, animals and in non-CF patients). Of particular interest were the origins of highly abundant CF strains detected in a recent epidemiological investigation [22]. Population-scaled recombination rates, evolutionary relationships and phylogenetic analyses were also conducted on isolates collected from each of these different settings.

Diversity

The 272 individual P. aeruginosa STs were distributed between environmental (n=83), animal (n=79), non-CF clinical (n=94) and CF patient (n=90) settings. Figure 3 shows that only 53 (19%) STs were shared among different ecological settings. Furthermore, five STs were detected in all four ecological settings (ST-155, ST-179, ST-253 (PA14), ST-266 and ST-381; Table S1), each of which had previously been detected elsewhere in the world [19], [27], [29], [31], [49], [50], [51], [52], [53].

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Figure 3

Venn diagram showing the number of individual sequence types (STs) detected in each of the ecological niches.

C: STs detected in cystic fibrosis patients; Human non-CF: STs detected in non-cystic fibrosis patients; Animal: STs detected in animals; Environment: STs detected in environmental samples.

Consistent with the Lower Brisbane River findings we observed no clustering of STs in CF patients compared with STs from broader ecological settings, suggesting that STs isolated from the CF lung are a random subsample of the overall population (Table 3). Initial PERMANOVA analysis of isolates from all ecological settings showed a significant difference in genetic diversity, although the contribution of the ecological setting to the variance was minimal. However, this finding was influenced mostly by the environmental and animal isolates, which each showed significant differences in genetic diversity compared to all other isolates, and a higher number of OTUs and greater degree of diversity. In contrast, we observed no statistically significant differences in ST variation amongst CF and non-CF human isolates when compared to isolates from all other ecological settings. Visual MDS comparisons of isolates from environmental, animal, and human non-CF and CF clinical settings also supported these findings (data not shown).

Table 3

Genetic diversity amongst Pseudomonas aeruginosa genotypes collected from each ecological setting, all Queensland sources and the Pseudomonas aeruginosa PubMLST database.

	Total numberof STs	Number of non-duplicate STs	Number of OTUs1	Simpson’s Index (95% CI)2	Shannon’s Index (95% CI)2	PERMANOVA Pseudo-F value3
Environment	83	52	15	0.33 (0.23–0.43)	1.6 (1.3–1.9)	4.87 (0.001)
Animal	79	53	11	0.48 (0.36–0.61)	1.2 (0.9–1.5)	2.16 (0.010)
Non-CF human	94	54	8	0.57 (0.45–0.68)	1.0 (0.7–1.2)	0.77 (0.581)
CF	90	62	5	0.60 (0.48–0.72)	0.8 (0.6–1.0)	1.88 (0.086)
Queensland - total	272	188	12	0.53 (0.45–0.62)	1.1 (0.9–1.3)
P. aeruginosa PubMLST database	1070	798	39	0.41 (0.37–0.45)	1.5 (1.4–1.6)	1.79 (0.094)4

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¹OTU, operational taxonomic unit containing groups of isolates that varied by a pairwise distance of <0.008.

²Simpson’s and Shannon’s indices were calculated for OTUs, because only non-duplicate STs were included for analysis.

³Comparison of each ecological source with the total dataset; P-values are presented in parentheses.

⁴Comparison of non-duplicate STs between Queensland MLST dataset and global dataset (P. aeruginosa PubMLST database [27]).

Recombination

Evidence of recombination was detected in five of seven loci (Table 5), and nucleotide substitution was approximately 19 times more likely to have occurred by recombination than point mutation. The clonal diversification method also confirmed that recombination played an important role in determining short-term genetic diversity. Of 18 variant alleles identified, 14 (78%) arose by recombination and four emerged by point mutation (Table 6). Overall, recombination generated new alleles 3.5 times more frequently than mutation, and the per nucleotide site r/m parameter was 9.51.

Table 5

Estimates of population-based mutation (θ) and recombination (ρ) rates among the 272 Pseudomonas aeruginosa sequence types using LDhat.¹

Gene	Nucleotides analysed	Parameters2						Likelihood permutation test3
		SS	Average PWD	θ	ρ	R/M
Concatenated	2874	36	14.4	5.82	110		18.9	<0.001
acsA	390	8	3.4	1.76	65		37	<0.001
aroE	495	10	4.4	2.2	11		5	0.004
guaA	372	7	2.1	1.56	35		22.4	0.024
mutL	441	4	1.7	0.9	23		25.5	<0.001
nuoD	366	7	1.9	1.69	250		148.3	0.648
ppsA	369	4	1.4	0.92	70		76.1	0.073
trpE	441	11	4.4	2.34	40		17.1	<0.001

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¹Only polymorphic sites with exactly two alleles were analysed.

²SS: number of segregating sites; PWD, pairwise distance; R/M: per nucleotide site recombination to mutation parameter.

³Likelihood permutation test results for the influence of recombination are presented as P-values.

Table 6

Relative contributions of recombination and mutation to recent clonal divergence.

Total variant alleles	Total nucleotide changes	Recombinational imports		Point mutations	Per fragment r/m parameter1	Per site r/m parameter2
		Variant alleles	Total nucleotide differences
18	43	143	38	4	3.51	9.51

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¹Per fragment r/m parameter: Estimated ratio of recombination to mutational events per gene fragment.

²Per site r/m parameter: Estimated ratio of the recombinational to mutational changes at an individual nucleotide site.

³Variant alleles, which arose through recombination and consisted of seven alleles with multiple nucleotide polymorphisms, and seven alleles showing single nucleotide polymorphisms.

eBURST analysis and minimum spanning tree construction

The 272 STs and related SLVs were grouped by eBURST into five BGs containing three to 11 STs and another 26 BGs of two STs each. In addition there were 196 singleton STs that lacked any SLVs (Table S1, Figure S3). The largest BG had 11 STs (43 isolates) originating from all four ecological settings and included the major CF strain ST-775 (AUST-02), two minor CF strains, three unique CF strains, and the equine genital strain ST-883. Of the other major CF-related strains, ST-649 (AUST-01) was a singleton ST, while ST-801 (AUST-06) shared BG-25 with an animal isolate ST-4. Frequently encountered genotypes ST-155, ST-253 (PA14), ST-266 and ST-274 each belonged to different BGs, while others including ST-179 and ST-381 represented singleton STs.

When a MST linking all TLV relationships was constructed, we observed a network of associations (Figure 4). In all, 177 (65%) STs were grouped into a single cluster, while only 18 remained as ungrouped singleton STs. Interestingly, the predicted founder of the largest cluster (minor CF strain ST-241) was also the putative ancestral founder of BG-01.

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Figure 4

goeBURST Minimal Spanning Tree of the 499 typeable Pseudomonas aeruginosa isolates (n=272 sequence types).

All sequence types (STs) were grouped up to the triple-locus variant level. Each circle corresponds to an individual ST and the dimensions of each circle are relative to the number of isolates belonging to that ST. Red, green, brown and blue circles represent isolates collected from patients with cystic fibrosis (CF), non-CF patients, animals and environmental samples, respectively. Whenever isolates of the same ST have a different ecological source, the number of isolates derived from the same source is proportional to the respective colour. Yellow coloured zones (labelled BG01 to BG05) represent the five predominant BURST groups that each consisted of three or more STs.

Phylogenetic analysis and tree congruence

To further elucidate the evolutionary relationships between STs we attempted to reconstruct ML phylogenies from individual housekeeping gene sequences and the concatenated sequences of all seven housekeeping genes. In order to test the validity of phylogenetic reconstruction, trees were reconstructed using 48 STs selected to encompass a broad range of genetic diversity. These STs included: (i) at least one ST from each BG, (ii) each of the abundant inter-niche STs, and (iii) a range of minor and major CF strains. Although the number of isolates utilised was supported by rarefaction analysis (Figure 2), this approach was rejected because the likelihood value of the phylogeny reconstructed from concatenated housekeeping gene sequences was lower than the likelihood values of phylogenies reconstructed from individual housekeeping genes. Similarly, the topology of the concatenated gene phylogeny was significantly different from the topology of individual gene phylogenies (SH test, P<0.05 for all pairwise comparisons).

In a further attempt to reconstruct a reliable phylogeny that encompassed the core P. aeruginosa genome we also compared the phylogeny of individual housekeeping genes to those constructed from all concatenated pairs and triplets of housekeeping genes. A tree reconstructed from concatenated guaA, mutL, and nuoD genes was the only phylogeny whose topology was not significantly different from guaA, mutL, and nuoD individual gene phylogenies. The resulting phylogeny was star-like, indicating evolution from a single common ancestor, or alternatively, a non-informative tree (Figure 5). Overall, there was a lack of congruence between trees constructed from sequences of individual loci indicating that different components of the core genome vary considerably with regards to their ancestry, presumably as a consequence of widespread recombination. Phylogenetic reconstruction using ClonalFrame (which removes portions of the nucleotide alignment subject to recombination) also resulted in a non-informative tree.

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Figure 5

Phylogenetic tree constructed from 48 concatenated guaA, mutL, and nuoD sequences indicating a star-like phylogeny.

Recombination

Earlier reports using qualitative methods, including a lack of congruence between phylogenies based on different loci, mosaic genetic structuring, and measures of linkage disequilibrium gave indirect evidence of recombination [29], [30], [32], [55], [56]. More recently, a study involving predominantly clinical isolates from five Mediterranean countries provided evidence of recombination occurring within P. aeruginosa populations and that recombination was more a common source of nucleotide substitution than point mutation [31]. Our data similarly demonstrate that alleles are at least 3.5 times more likely to change by recombination than mutation. Moreover, we found significant evidence of recombination among a subset of environmental isolates collected from the Brisbane River. Together, our data indicate that P. aeruginosa has a similar structure to other pathogens with highly recombinant populations, such as Neisseria meningitidis, Streptococcus pneumoniae, and Vibrio parahaemolyticus [43], [57], [58].

Not unexpectedly, we found recombination to be sufficiently frequent to destroy any overall phylogenetic information [59]. There was no congruence between trees constructed from sequences of individual loci, indicating that different components of the core genome vary considerably in their ancestry. Consequently, traditional phylogenetic clustering techniques are unsuitable for determining long-term epidemiological relationships and evolutionary pathways for P. aeruginosa. Indeed, employing such approaches, particularly where phenotypic characters are mapped onto gene trees [32], may generate erroneous assumptions [59]. Instead, clustering techniques that associate STs by allelic designation should be used for identifying recent evolutionary patterns.

Recombination is the most likely mechanism for failing to identify an overall association between genotype and ecological setting. The absence of population substructures, such as biovars or delineated ecotypes, suggests that irrespective of strain origin P. aeruginosa is evolving as a single cohesive genetic group. A recent study of diversity across the genus Pseudomonas concluded that of all the species, only P. aeruginosa conformed to a ‘clear, compact, defined species’ [60]. However, just what maintains this integrity, aside from recombination is uncertain.

Genotypic Diversity

The discovery of both major and minor CF-related P. aeruginosa strains is also consistent with previous reports [19], [20], [21]. However, while previously known STs, such as ST-155, ST-179 and ST-274, were encountered on multiple occasions and in different ecological settings, other abundant STs were uniquely Australian [e.g. ST-775 (AUST-02) and ST-801 (AUST-06)]. This reinforces the hypothesis of CF-related strains being a random subset of the total P. aeruginosa population and where chance colonisation events specific to different geographical regions also play a role. Once genetic adaptation to the CF lung occurs [61], [62], a small number of genotypes may develop an enhanced ability for person-to-person transmission. Indeed, evidence of transmission and evolution was also evident in the present study. For example, ST-775 (AUST-02) was isolated on numerous occasions from CF patients and it showed close evolutionary relationships to several STs that are likely to have evolved from this common CF genotype.

The major Queensland CF strains [ST-649 (AUST-01), ST-775 (AUST-02) and ST-801 (AUST-06)] were isolated from CF patients, but not from other sources, suggesting patient-to-patient transmission has occurred. The same holds true for the major equine-associated strain (ST-883) that was isolated exclusively from the horse reproductive tract [54]. These findings are consistent with earlier reports of ST-649 (AUST-01), where despite it being abundant in CF patients, repeated microbiological surveys failed to identify it in the healthcare environment [63]. Such observations are in marked contrast with other previously known CF-associated STs, such as ST-155, ST-179, ST-253 (PA14) and ST-274, that we isolated from many CF patients and multiple other ecological settings.

While isolates belonging to ST-155, ST-179, ST-253 (PA14) and ST-274 are likely to show substantive variation at other loci, particularly among their accessory genes [29], [31], [34], finding STs in Queensland showing identity over approximately 3,000 nucleotides to previously recorded STs is remarkable. While substantiating the existence of highly abundant STs, this study shows that such STs are truly globally distributed and in some cases would appear to have persisted for many years. However, the existence of global genotypes within a freely recombining bacterial population is difficult to reconcile [64]. In the face of recombination, strains or large BGs (clonal complexes) should be transient and yet ST-253 (PA14), for example, was first isolated from a human infection in the United States more than 15-years ago [65]. ST-253 (PA14) is common throughout the Northern Hemisphere [27], [29], [31], [50], and in the present study was isolated on 15 occasions from a broad range of environmental, animal and clinical settings. The most parsimonious explanation invokes an extraordinary population expansion of a small number of lineages in a brief period of time with these abundant genotypes then achieving global representation. However, just what would cause such an explosive dispersal across environments that include river systems in Queensland is far from clear.

The finding of abundant environmental STs has been suggested previously as the cause of their prevalence in CF patients [32], [66]. Our findings both support and question this claim. Indeed, strains such as ST-253 (PA14) are widespread in other ecological settings, thus increasing the chance that they will also infect the CF lung. However, despite their widespread presence in other ecological settings, these abundant strains still represent only unique or minor CF strains present in relatively small clusters of CF patients. In contrast, the most common CF strains in this geographic region [ST-649 (AUST-01), ST-775 (AUST-02) and ST-801 (AUST-06)] were not encountered in other ecological settings. These findings are consistent with a recent Dutch study, which suggested that common CF strains, ST-406 and ST-497, exhibited high-level host specificity for the CF lung microenvironment [24].

Our study offers further insights, when placed in context of the entire P. aeruginosa population reflected by the PubMLST database. First, the diversity shown in the present study did not differ significantly from that of the global collection. This is consistent with findings from a Belgian river system [7]. Interestingly though, we did not find a positive relationship between river pollution and the detection of P. aeruginosa as reported in the Belgian study [7]. Moreover, approximately 15% of river STs were present at multiple collection sites, including ST-863, which was cultured from both the Lower Brisbane and Logan Rivers. Finding that local diversity was no different than global diversity is important for understanding the apportionment of P. aeruginosa diversity across space. Second, although there was no close association between genotype and environment, some STs, many associated with CF, have diverged from a set of closely related STs. While extensive recombination means the overall relationship amongst these large BGs (clonal complexes) is unknown, the existence of such complexes suggests that certain P. aeruginosa genotypes shared between CF patients have become specifically adapted to the CF lung [67].

We are grateful to all the participants, research and clinical staff, and clinical microbiology laboratories at The Prince Charles Hospital, Royal Children’s Hospital, Mater Adult Hospital, Mater Children’s Hospital, and Gold Coast Hospital for the provision of clinical samples and CF isolates. We also thank staff from the Pathology Queensland Central Laboratory, Queensland Health Public Health Microbiology Laboratory, IDEXX Laboratories Pty. Ltd, The University of Queensland Diagnostic Laboratory, Professor Claire Wainwright and Ms Snehal Anuj for the environmental, animal and non-CF human isolates they contributed to the study. PBR is a James Cook Research Fellow and SCB is a Health Research Fellow (Office of Health and Medical Research, Queensland Health). This publication made use of the Pseudomonas aeruginosa PubMLST website (http://pubmlst.org/paeruginosa/) developed by Keith Jolley and sited at the University of Oxford [35]. The development of this site has been funded by the Wellcome Trust.