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Six Novel O Genotypes from Shiga Toxin-Producing Escherichia coli

Overview of attention for article published in Frontiers in Microbiology, May 2016
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Title
Six Novel O Genotypes from Shiga Toxin-Producing Escherichia coli
Published in
Frontiers in Microbiology, May 2016
DOI 10.3389/fmicb.2016.00765
Pubmed ID
Authors

Atsushi Iguchi, Sunao Iyoda, Kazuko Seto, Hironobu Nishii, Makoto Ohnishi, Hirohisa Mekata, Yoshitoshi Ogura, Tetsuya Hayashi

Abstract

Serotyping is one of the typing techniques used to classify strains within the same species. O-serogroup diversification shows a strong association with the genetic diversity of O-antigen biosynthesis genes. In a previous study, based on the O-antigen biosynthesis gene cluster (O-AGC) sequences of 184 known Escherichia coli O serogroups (from O1 to O187), we developed a comprehensive and practical molecular O serogrouping (O genotyping) platform using a polymerase chain reaction (PCR) method, named E. coli O-genotyping PCR. Although, the validation assay using the PCR system showed that most of the tested strains were successfully classified into one of the O genotypes, it was impossible to classify 6.1% (35/575) of the strains, suggesting the presence of novel O genotypes. In this study, we conducted sequence analysis of O-AGCs from O-genotype untypeable Shiga toxin-producing E. coli (STEC) strains and identified six novel O genotypes; OgN1, OgN8, OgN9, OgN10, OgN12 and OgN31, with unique wzx and/or wzy O-antigen processing gene sequences. Additionally, to identify these novel O-genotypes, we designed specific PCR primers. A screen of O genotypes using O-genotype untypeable strains showed 13 STEC strains were classified into five novel O genotypes. The O genotyping at the molecular level of the O-AGC would aid in the characterization of E. coli isolates and will assist future studies in STEC epidemiology and phylogeny.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 37%
Researcher 4 11%
Student > Postgraduate 4 11%
Professor > Associate Professor 2 6%
Student > Master 2 6%
Other 4 11%
Unknown 6 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 23%
Biochemistry, Genetics and Molecular Biology 7 20%
Immunology and Microbiology 5 14%
Medicine and Dentistry 3 9%
Chemistry 2 6%
Other 3 9%
Unknown 7 20%
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 21 May 2016.
All research outputs
#18,459,684
of 22,873,031 outputs
Outputs from Frontiers in Microbiology
#19,377
of 24,889 outputs
Outputs of similar age
#250,130
of 333,293 outputs
Outputs of similar age from Frontiers in Microbiology
#421
of 573 outputs
Altmetric has tracked 22,873,031 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,889 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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