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Genotyping bacterial and fungal pathogens using sequence variation in the gene for the CCA-adding enzyme

Overview of attention for article published in BMC Microbiology, March 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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1 blog
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3 X users

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Title
Genotyping bacterial and fungal pathogens using sequence variation in the gene for the CCA-adding enzyme
Published in
BMC Microbiology, March 2016
DOI 10.1186/s12866-016-0670-2
Pubmed ID
Authors

Paul Franz, Heike Betat, Mario Mörl

Abstract

To allow an immediate treatment of an infection with suitable antibiotics and bactericides or fungicides, there is an urgent need for fast and precise identification of the causative human pathogens. Methods based on DNA sequence comparison like 16S rRNA analysis have become standard tools for pathogen verification. However, the distinction of closely related organisms remains a challenging task. To overcome such limitations, we identified a new genomic target sequence located in the single copy gene for tRNA nucleotidyltransferase fulfilling the requirements for a ubiquitous, yet highly specific DNA marker. In the present study, we demonstrate that this sequence marker has a higher discriminating potential than commonly used genotyping markers in pro- as well as eukaryotes, underscoring its applicability as an excellent diagnostic tool in infectology. Based on phylogenetic analyses, a region within the gene for tRNA nucleotidyltransferase (CCA-adding enzyme) was identified as highly heterogeneous. As prominent examples for pro- and eukaryotic pathogens, several Vibrio and Aspergillus species were used for genotyping and identification in a multiplex PCR approach followed by gel electrophoresis and fluorescence-based product detection. Compared to rRNA analysis, the selected gene region of the tRNA nucleotidyltransferase revealed a seven to 30-fold higher distinction potential between closely related Vibrio or Aspergillus species, respectively. The obtained data exhibit a superb genome specificity in the diagnostic analysis. Even in the presence of a 1,000-fold excess of human genomic DNA, no unspecific amplicons were produced. These results indicate that a relatively short segment of the coding region for tRNA nucleotidyltransferase has a higher discriminatory potential than most established diagnostic DNA markers. Besides identifying microbial pathogens in infections, further possible applications of this new marker are food hygiene controls or metagenome analyses.

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 28%
Student > Master 6 24%
Student > Ph. D. Student 2 8%
Student > Bachelor 2 8%
Professor 1 4%
Other 1 4%
Unknown 6 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 24%
Biochemistry, Genetics and Molecular Biology 6 24%
Environmental Science 2 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 8%
Medicine and Dentistry 2 8%
Other 1 4%
Unknown 6 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 24 March 2016.
All research outputs
#3,671,763
of 24,885,505 outputs
Outputs from BMC Microbiology
#332
of 3,434 outputs
Outputs of similar age
#56,898
of 306,793 outputs
Outputs of similar age from BMC Microbiology
#10
of 61 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,434 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 90% 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 306,793 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.