↓ Skip to main content

Whole Genome Sequencing for Genomics-Guided Investigations of Escherichia coli O157:H7 Outbreaks

Overview of attention for article published in Frontiers in Microbiology, June 2016
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
7 news outlets
twitter
4 X users

Readers on

mendeley
69 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Whole Genome Sequencing for Genomics-Guided Investigations of Escherichia coli O157:H7 Outbreaks
Published in
Frontiers in Microbiology, June 2016
DOI 10.3389/fmicb.2016.00985
Pubmed ID
Authors

Brigida Rusconi, Fatemeh Sanjar, Sara S. K. Koenig, Mark K. Mammel, Phillip I. Tarr, Mark Eppinger

Abstract

Multi isolate whole genome sequencing (WGS) and typing for outbreak investigations has become a reality in the post-genomics era. We applied this technology to strains from Escherichia coli O157:H7 outbreaks. These include isolates from seven North America outbreaks, as well as multiple isolates from the same patient and from different infected individuals in the same household. Customized high-resolution bioinformatics sequence typing strategies were developed to assess the core genome and mobilome plasticity. Sequence typing was performed using an in-house single nucleotide polymorphism (SNP) discovery and validation pipeline. Discriminatory power becomes of particular importance for the investigation of isolates from outbreaks in which macrogenomic techniques such as pulse-field gel electrophoresis or multiple locus variable number tandem repeat analysis do not differentiate closely related organisms. We also characterized differences in the phage inventory, allowing us to identify plasticity among outbreak strains that is not detectable at the core genome level. Our comprehensive analysis of the mobilome identified multiple plasmids that have not previously been associated with this lineage. Applied phylogenomics approaches provide strong molecular evidence for exceptionally little heterogeneity of strains within outbreaks and demonstrate the value of intra-cluster comparisons, rather than basing the analysis on archetypal reference strains. Next generation sequencing and whole genome typing strategies provide the technological foundation for genomic epidemiology outbreak investigation utilizing its significantly higher sample throughput, cost efficiency, and phylogenetic relatedness accuracy. These phylogenomics approaches have major public health relevance in translating information from the sequence-based survey to support timely and informed countermeasures. Polymorphisms identified in this work offer robust phylogenetic signals that index both short- and long-term evolution and can complement currently employed typing schemes for outbreak ex- and inclusion, diagnostics, surveillance, and forensic studies.

X Demographics

X Demographics

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 readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 1%
Unknown 68 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 19%
Student > Ph. D. Student 10 14%
Student > Master 8 12%
Student > Bachelor 6 9%
Other 5 7%
Other 16 23%
Unknown 11 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 28%
Biochemistry, Genetics and Molecular Biology 11 16%
Medicine and Dentistry 7 10%
Immunology and Microbiology 5 7%
Computer Science 3 4%
Other 8 12%
Unknown 16 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 54. 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 25 July 2016.
All research outputs
#661,560
of 22,880,230 outputs
Outputs from Frontiers in Microbiology
#332
of 24,902 outputs
Outputs of similar age
#14,342
of 351,542 outputs
Outputs of similar age from Frontiers in Microbiology
#9
of 514 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 24,902 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done particularly well, scoring higher than 98% 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 351,542 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 514 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.