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High-Resolution Melting Analysis for Rapid Detection of Sequence Type 131 Escherichia coli

Overview of attention for article published in Antimicrobial Agents and Chemotherapy, May 2017
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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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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32 Mendeley
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Article details
Title
High-Resolution Melting Analysis for Rapid Detection of Sequence Type 131 Escherichia coli
Published in
Antimicrobial Agents and Chemotherapy, May 2017
DOI 10.1128/aac.00265-17
Pubmed ID
Authors
Abstract

IntroductionE. coli belonging to sequence type 131 clonal complex (ST131) have been associated with the global distribution of fluoroquinolone and β-lactam resistance. Whole genome sequencing and multi-locus sequence typing identify sequence type but are expensive when evaluating large numbers of samples. This study was designed to develop a cost-effective screening tool using high resolution melting (HRM) analysis to differentiate ST131 from non-ST-131 E. coli in large sample populations in the absence of sequence analysis.Methods The method was optimized using DNA from twelve E. coli isolates. Singleplex PCR was performed using 10 ng of DNA, Type-it HRM buffer and Multi-Locus Sequence Typing primers followed by multiplex PCR. Amplicon sizes ranged from 630-737 bp. Melt temperature peaks were determined by performing HRM analysis at 0.1°C resolution from 50-95°C on a Rotor-Gene Q 5-Plex HRM system. Derivative melt curves were compared between sequence types and analyzed by principal component analysis. A blinded study of 191 E. coli of ST131 and unknown sequence types validated this methodology.Results This methodology returned 99.2% specificity (True Negative=124, False Positive=1) and 100% sensitivity (True Positive=66, False Negative=0).Conclusion This HRM methodology distinguishes ST131 from non-ST131 E. coli without sequence analysis. The analysis can be accomplished in about 3 hours in any laboratory with a HRM-capable instrument and principal component analysis software. Therefore, this assay is a fast and cost-effective alternative to sequencing-based ST131 identification.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 9 28%
Student > Doctoral Student 4 13%
Student > Master 3 9%
Researcher 3 9%
Other 2 6%
Other 4 13%
Unknown 7 22%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 8 25%
Biochemistry, Genetics and Molecular Biology 6 19%
Medicine and Dentistry 4 13%
Veterinary Science and Veterinary Medicine 1 3%
Computer Science 1 3%
Other 3 9%
Unknown 9 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 02 May 2023.
All research outputs
#3,998,836
of 33,351,181 outputs
Outputs from Antimicrobial Agents and Chemotherapy
#2,277
of 18,180 outputs
Outputs of similar age
#53,787
of 354,375 outputs
Outputs of similar age from Antimicrobial Agents and Chemotherapy
#32
of 196 outputs
Altmetric has tracked 33,351,181 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 18,180 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done well, scoring higher than 87% 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 354,375 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 84% of its contemporaries.
We're also able to compare this research output to 196 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.