Dataset Information

The population genetics of Pseudomonas aeruginosa isolates from different patient populations exhibits high-level host specificity.

ABSTRACT:

Objective

To determine whether highly prevalent P. aeruginosa sequence types (ST) in Dutch cystic fibrosis (CF) patients are specifically linked to CF patients we investigated the population structure of P. aeruginosa from different clinical backgrounds. We first selected the optimal genotyping method by comparing pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST) and multilocus variable number tandem-repeat analysis (MLVA).

Methods

Selected P. aeruginosa isolates (n = 60) were genotyped with PFGE, MLST and MLVA to determine the diversity index (DI) and congruence (adjusted Rand and Wallace coefficients). Subsequently, isolates from patients admitted to two different ICUs (n = 205), from CF patients (n = 100) and from non-ICU, non-CF patients (n = 58, of which 19 were community acquired) were genotyped with MLVA to determine distribution of genotypes and genetic diversity.

Results

Congruence between the typing methods was >79% and DIs were similar and all >0.963. Based on costs, ease, speed and possibilities to compare results between labs an adapted MLVA scheme called MLVA9-Utrecht was selected as the preferred typing method. In 363 clinical isolates 252 different MLVA types (MTs) were identified, indicating a highly diverse population (DI ?= 0.995; CI ?= 0.993-0.997). DI levels were similarly high in the diverse clinical sources (all >0.981) and only eight genotypes were shared. MTs were highly specific (>80%) for the different patient populations, even for similar patient groups (ICU patients) in two distinct geographic regions, with only three of 142 ICU genotypes detected in both ICUs. The two major CF clones were unique to CF patients.

Conclusion

The population structure of P. aeruginosa isolates is highly diverse and population specific without evidence for a core lineage in which major CF, hospital or community clones co-cluster. The two genotypes highly prevalent among Dutch CF patients appeared unique to CF patients, suggesting specific adaptation of these clones to the CF lung.

SUBMITTER: van Mansfeld R

PROVIDER: S-EPMC2957436 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Publications

The population genetics of Pseudomonas aeruginosa isolates from different patient populations exhibits high-level host specificity.

van Mansfeld Rosa R Jongerden Irene I Bootsma Martin M Buiting Anton A Bonten Marc M Willems Rob R

PloS one 20101019 10

<h4>Objective</h4>To determine whether highly prevalent P. aeruginosa sequence types (ST) in Dutch cystic fibrosis (CF) patients are specifically linked to CF patients we investigated the population structure of P. aeruginosa from different clinical backgrounds. We first selected the optimal genotyping method by comparing pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST) and multilocus variable number tandem-repeat analysis (MLVA).<h4>Methods</h4>Selected P. aeruginosa i ...[more]

PMID: 20976062

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Project description:The opportunistic pathogen Pseudomonas aeruginosa is ubiquitous in the environment, and in humans, it is capable of causing acute or chronic infections. In the natural environment, predation by bacterivorous protozoa represents a primary threat to bacteria. Here, we determined the impact of long-term exposure of P. aeruginosa to predation pressure. P. aeruginosa persisted when coincubated with the bacterivorous Acanthamoeba castellanii for extended periods and produced genetic and phenotypic variants. Sequencing of late-stage amoeba-adapted P. aeruginosa isolates demonstrated single nucleotide polymorphisms within genes that encode known virulence factors, and this correlated with a reduction in expression of virulence traits. Virulence for the nematode Caenorhabditis elegans was attenuated in late-stage amoeba-adapted P. aeruginosa compared to early-stage amoeba-adapted and nonadapted counterparts. Further, late-stage amoeba-adapted P. aeruginosa showed increased competitive fitness and enhanced survival in amoebae as well as in macrophage and neutrophils. Interestingly, our findings indicate that the selection imposed by amoebae resulted in P. aeruginosa isolates with reduced virulence and enhanced fitness, similar to those recovered from chronic cystic fibrosis infections. Thus, predation by protozoa and long-term colonization of the human host may represent similar environments that select for similar losses of gene function. IMPORTANCE Pseudomonas aeruginosa is an opportunistic pathogen that causes both acute infections in plants and animals, including humans, and chronic infections in immunocompromised and cystic fibrosis patients. This bacterium is commonly found in soils and water, where bacteria are constantly under threat of being consumed by bacterial predators, e.g., protozoa. To escape being killed, bacteria have evolved a suite of mechanisms that protect them from being consumed or digested. Here, we examined the effect of long-term predation on the genotypes and phenotypes expressed by P. aeruginosa. We show that long-term coincubation with protozoa gave rise to mutations that resulted in P. aeruginosa becoming less pathogenic. This is particularly interesting as similar mutations arise in bacteria associated with chronic infections. Importantly, the genetic and phenotypic traits possessed by late-stage amoeba-adapted P. aeruginosa are similar to those observed in isolates obtained from chronic cystic fibrosis infections. This notable overlap in adaptation to different host types suggests similar selection pressures among host cell types as well as similar adaptation strategies.

Dataset Information

The population genetics of Pseudomonas aeruginosa isolates from different patient populations exhibits high-level host specificity.

Objective

Methods

Results

Conclusion

Publications

The population genetics of Pseudomonas aeruginosa isolates from different patient populations exhibits high-level host specificity.

Similar Datasets

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