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Genotypic and phenotypic analyses of a Pseudomonas aeruginosa chronic bronchiectasis isolate reveal differences from cystic fibrosis and laboratory strains

Overview of attention for article published in BMC Genomics, October 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

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9 tweeters

Citations

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27 Dimensions

Readers on

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147 Mendeley
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Title
Genotypic and phenotypic analyses of a Pseudomonas aeruginosa chronic bronchiectasis isolate reveal differences from cystic fibrosis and laboratory strains
Published in
BMC Genomics, October 2015
DOI 10.1186/s12864-015-2069-0
Pubmed ID
Authors

John J. Varga, Mariette Barbier, Xavier Mulet, Piotr Bielecki, Jennifer A. Bartell, Joshua P. Owings, Inmaculada Martinez-Ramos, Lauren E. Hittle, Michael R. Davis, F. Heath Damron, George W. Liechti, Jacek Puchałka, Vitor A. P. Martins dos Santos, Robert K. Ernst, Jason A. Papin, Sebastian Albertí, Antonio Oliver, Joanna B. Goldberg

Abstract

Pseudomonas aeruginosa is an environmentally ubiquitous Gram-negative bacterium and important opportunistic human pathogen, causing severe chronic respiratory infections in patients with underlying conditions such as cystic fibrosis (CF) or bronchiectasis. In order to identify mechanisms responsible for adaptation during bronchiectasis infections, a bronchiectasis isolate, PAHM4, was phenotypically and genotypically characterized. This strain displays phenotypes that have been associated with chronic respiratory infections in CF including alginate over-production, rough lipopolysaccharide, quorum-sensing deficiency, loss of motility, decreased protease secretion, and hypermutation. Hypermutation is a key adaptation of this bacterium during the course of chronic respiratory infections and analysis indicates that PAHM4 encodes a mutated mutS gene responsible for a ~1,000-fold increase in mutation rate compared to wild-type laboratory strain P. aeruginosa PAO1. Antibiotic resistance profiles and sequence data indicate that this strain acquired numerous mutations associated with increased resistance levels to β-lactams, aminoglycosides, and fluoroquinolones when compared to PAO1. Sequencing of PAHM4 revealed a 6.38 Mbp genome, 5.9 % of which were unrecognized in previously reported P. aeruginosa genome sequences. Transcriptome analysis suggests a general down-regulation of virulence factors, while metabolism of amino acids and lipids is up-regulated when compared to PAO1 and metabolic modeling identified further potential differences between PAO1 and PAHM4. This work provides insights into the potential differential adaptation of this bacterium to the lung of patients with bronchiectasis compared to other clinical settings such as cystic fibrosis, findings that should aid the development of disease-appropriate treatment strategies for P. aeruginosa infections.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Denmark 1 <1%
Canada 1 <1%
Brazil 1 <1%
Unknown 142 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 20%
Student > Master 28 19%
Student > Bachelor 22 15%
Researcher 18 12%
Student > Doctoral Student 9 6%
Other 27 18%
Unknown 14 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 28%
Biochemistry, Genetics and Molecular Biology 29 20%
Immunology and Microbiology 21 14%
Medicine and Dentistry 16 11%
Engineering 4 3%
Other 19 13%
Unknown 17 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 June 2016.
All research outputs
#4,582,870
of 15,920,653 outputs
Outputs from BMC Genomics
#2,427
of 8,860 outputs
Outputs of similar age
#81,871
of 287,009 outputs
Outputs of similar age from BMC Genomics
#294
of 998 outputs
Altmetric has tracked 15,920,653 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 8,860 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 287,009 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 998 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.