Evidence map›Paper›PMID 19706365›Full record

ReviewHuman genomics2009

Comparative transcriptome analyses of Pseudomonas aeruginosa.

Deepak Balasubramanian, Kalai Mathee

Abstract readComparative StudyReview
In one paragraph

Review in Human genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
  2. Oxidative Stress Response inPathogens (Basel, Switzerland) · 2021
    Review
  3. Article
  4. Determining the Different Mechanisms Used byFrontiers in microbiology · 2020
    Article
  5. Transcriptomic Response inInternational journal of microbiology · 2020
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Why is Pseudomonas aeruginosa a pathogen?F1000 biology reports · 2010
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Deepak BalasubramanianDepartment of Biological Sciences, College of Arts and Science, Florida International University, Miami, FL 33199, USA.
Kalai Mathee

Funding

Regulation of P. aeruginosa PoxB Oxacillinase by AmpR and a Two-Component SystemSC1AI081376 · NIAID · FLORIDA INTERNATIONAL UNIVERSITY · PI MATHEE, KALAI · 2008 to 2011
$1.2M
NIAID NIH HHS SC1 AI081376PHS HHS M083677
6 · The paper itself

Abstract

One of the hallmarks of bacterial survival is their ability to adapt rapidly to changing environmental conditions. Niche adaptation is a response to the signals received that are relayed, often to regulators that modulate gene expression. In the post-genomic era, DNA microarrays are used to study the dynamics of gene expression on a global scale. Numerous studies have used Pseudomonas aeruginosa--a Gram-negative environmental and opportunistic human pathogenic bacterium--as the model organism in whole-genome transcriptome analysis. This paper reviews the transcriptome studies that have led to immense advances in our understanding of the biology of this intractable human pathogen. Comparative analysis of 23 P. aeruginosa transcriptome studies has led to the identification of a unique set of genes that are signal specific and a core set that is differentially regulated. The 303 genes in the core set are involved in bacterial homeostasis, making them attractive therapeutic targets.

Indexed as

BiofilmsHumansOligonucleotide Array Sequence AnalysisOsmotic PressurePseudomonas aeruginosaQuorum SensingRNA, BacterialRNA, MessengerVirulenceRNA, BacterialRNA, Messenger

Identifiers

PMID19706365
PMCPMC2897818

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.