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Differentiation of Salmonella strains from the SARA, SARB and SARC reference collections by using three genes PCR-RFLP and the 2100 Agilent Bioanalyzer

Overview of attention for article published in Frontiers in Microbiology, August 2014
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Title
Differentiation of Salmonella strains from the SARA, SARB and SARC reference collections by using three genes PCR-RFLP and the 2100 Agilent Bioanalyzer
Published in
Frontiers in Microbiology, August 2014
DOI 10.3389/fmicb.2014.00417
Pubmed ID
Authors

Ángel A. Soler-García, Antonio J. De Jesús, Kishana Taylor, Eric W. Brown

Abstract

Rapid molecular typing methods are important tools in surveillance and outbreak investigations of human Salmonella infections. Here we described the development of a three-genes PCR-RFLP typing method for the differentiation of Salmonella species, subspecies and serovars using the Agilent 2100 Bioanalyzer. The fliC, gnd, and mutS genes were PCR-amplified in 160 Salmonella strains representing the two Salmonella species, six subspecies, and 41 different serovars of S. enterica subspecies enterica. PCR products were individually cut with two different restriction enzymes and the resulting 930 restriction patterns were collected using the Agilent 2100 Bioanalyzer followed by cluster analysis. Both species of Salmonella were differentiated by conventional PCR. All of S. bongori tested were gnd PCR negative due to a mismatch at the 3'-end in one the PCR primers. Salmonella subspecies were differentiated into third-teen homogeneous groups representing each of the six subspecies by cluster analysis of restriction patterns generated from the mutS gene cut with AciI. S. enterica subspecies enterica serovars were further differentiated by the combination of the three target genes and five out the six sets of restriction patterns with a discriminatory power of 0.9725 by cluster analysis. The combined RFLP results of five sets of restriction patterns allowed us to assign each of the 160 strains to one of 128 restriction types. During inoculation studies we were able to identify S. Saintpaul and Typhimurium from 24 h pre-enrichment samples using the described method. The use of fliC, gnd, and mutS PCR-RFLP with the Agilent 2100 Bioanalyzer can provide an accessible and automated alternative method for differentiation of Salmonella pathogens.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 25%
Student > Master 4 17%
Researcher 4 17%
Student > Bachelor 2 8%
Unspecified 1 4%
Other 2 8%
Unknown 5 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 42%
Biochemistry, Genetics and Molecular Biology 3 13%
Medicine and Dentistry 2 8%
Immunology and Microbiology 2 8%
Veterinary Science and Veterinary Medicine 1 4%
Other 1 4%
Unknown 5 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 26 August 2014.
All research outputs
#15,877,484
of 24,192,521 outputs
Outputs from Frontiers in Microbiology
#15,331
of 27,297 outputs
Outputs of similar age
#131,404
of 235,333 outputs
Outputs of similar age from Frontiers in Microbiology
#99
of 169 outputs
Altmetric has tracked 24,192,521 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 27,297 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 235,333 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 169 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.