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Examination of clinical and environmental Vibrio parahaemolyticus isolates by multi-locus sequence typing (MLST) and multiple-locus variable-number tandem-repeat analysis (MLVA)

Overview of attention for article published in Frontiers in Microbiology, June 2015
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Title
Examination of clinical and environmental Vibrio parahaemolyticus isolates by multi-locus sequence typing (MLST) and multiple-locus variable-number tandem-repeat analysis (MLVA)
Published in
Frontiers in Microbiology, June 2015
DOI 10.3389/fmicb.2015.00564
Pubmed ID
Authors

Catharina H. M. Lüdeke, Narjol Gonzalez-Escalona, Markus Fischer, Jessica L. Jones

Abstract

Vibrio parahaemolyticus is a leading cause of seafood-borne infections in the US. This organism has a high genetic diversity that complicates identification of strain relatedness and epidemiological investigations. However, sequence-based analysis methods are promising tools for these identifications. In this study, Multi-Locus Sequence Typing (MLST) and Multiple-Locus Variable-Number Tandem-Repeat Analysis (MLVA) was performed on 58 V. parahaemolyticus isolates (28 of oyster and 30 of clinical origin), to identify differences in phylogeny. The results obtained by both methods were compared to Pulsed-Field Gel Electrophoresis (PFGE) patterns determined in a previous study. Forty-one unique sequence types (STs) were identified by MLST among the 58 isolates. Almost half of the isolates (22) belonged to a new ST and added to the MLST database. A ST could not be generated for 5 (8.6%) isolates, primarily due to an untypable recA locus. Analysis with eBURST did not identify any clonal complex among the strains analyzed and revealed 37 singeltons with 4 of them forming 2 groups (1 of them SLV, and the other a DLV). An established MLVA assay, targeting 12 total genes through three separate 4-plex PCRs, was successfully adapted to high resolution melt (HRM) analysis with faster and easier experimental setup; resulting in 58 unique melt curve patterns. HRM-MLVA was capable of differentiating isolates within the same PFGE cluster and having the same ST. Conclusively, combining the three methods PFGE, MLST, and HRM-MLVA, for the phylogenetic analysis of V. parahaemolyticus resulted in a high resolution subtyping scheme for V. parahaemolyticus. This scheme will be useful as a phylogenetic research tool and as an improved method for outbreak investigations for V. parahaemolyticus.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 28%
Student > Ph. D. Student 7 15%
Researcher 5 11%
Student > Bachelor 5 11%
Student > Doctoral Student 4 9%
Other 2 4%
Unknown 11 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 32%
Biochemistry, Genetics and Molecular Biology 10 21%
Immunology and Microbiology 5 11%
Veterinary Science and Veterinary Medicine 3 6%
Unspecified 1 2%
Other 1 2%
Unknown 12 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 May 2015.
All research outputs
#23,715,077
of 26,397,269 outputs
Outputs from Frontiers in Microbiology
#24,995
of 30,274 outputs
Outputs of similar age
#241,200
of 280,922 outputs
Outputs of similar age from Frontiers in Microbiology
#307
of 386 outputs
Altmetric has tracked 26,397,269 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 30,274 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 1st percentile – i.e., 1% 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 280,922 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 386 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.