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The Validation and Implications of Using Whole Genome Sequencing as a Replacement for Traditional Serotyping for a National Salmonella Reference Laboratory

Overview of attention for article published in Frontiers in Microbiology, June 2017
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Title
The Validation and Implications of Using Whole Genome Sequencing as a Replacement for Traditional Serotyping for a National Salmonella Reference Laboratory
Published in
Frontiers in Microbiology, June 2017
DOI 10.3389/fmicb.2017.01044
Pubmed ID
Authors

Chris A. Yachison, Catherine Yoshida, James Robertson, John H. E. Nash, Peter Kruczkiewicz, Eduardo N. Taboada, Matthew Walker, Aleisha Reimer, Sara Christianson, Anil Nichani, The PulseNet Canada Steering Committee, Celine Nadon, Ana Paccagnella, Linda Hoang, Linda Chui, Paul Levett, Ryan McDonald, John Wylie, David Alexander, Vanessa Allen, Anne Maki, Sadjia Bekal, Ross Davidson, Elspeth Nickerson, Janet Reid, Laura Gilbert, Greg German, Moe Elmufti, Sean Quinlan, Cathy Carrillo, Ray Allain, Franco Pagotto, Lorelee Tschetter, Kim Ziebell

Abstract

Salmonella serotyping remains the gold-standard tool for the classification of Salmonella isolates and forms the basis of Canada's national surveillance program for this priority foodborne pathogen. Public health officials have been increasingly looking toward whole genome sequencing (WGS) to provide a large set of data from which all the relevant information about an isolate can be mined. However, rigorous validation and careful consideration of potential implications in the replacement of traditional surveillance methodologies with WGS data analysis tools is needed. Two in silico tools for Salmonella serotyping have been developed, the Salmonella in silico Typing Resource (SISTR) and SeqSero, while seven gene MLST for serovar prediction can be adapted for in silico analysis. All three analysis methods were assessed and compared to traditional serotyping techniques using a set of 813 verified clinical and laboratory isolates, including 492 Canadian clinical isolates and 321 isolates of human and non-human sources. Successful results were obtained for 94.8, 88.2, and 88.3% of the isolates tested using SISTR, SeqSero, and MLST, respectively, indicating all would be suitable for maintaining historical records, surveillance systems, and communication structures currently in place and the choice of the platform used will ultimately depend on the users need. Results also pointed to the need to reframe serotyping in the genomic era as a test to understand the genes that are carried by an isolate, one which is not necessarily congruent with what is antigenically expressed. The adoption of WGS for serotyping will provide the simultaneous collection of information that can be used by multiple programs within the current surveillance paradigm; however, this does not negate the importance of the various programs or the role of serotyping going forward.

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The data shown below were collected from the profiles of 3 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 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 93 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 20%
Student > Ph. D. Student 15 16%
Student > Master 11 12%
Student > Bachelor 5 5%
Other 5 5%
Other 9 10%
Unknown 29 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 22%
Agricultural and Biological Sciences 19 20%
Immunology and Microbiology 7 8%
Veterinary Science and Veterinary Medicine 5 5%
Medicine and Dentistry 4 4%
Other 7 8%
Unknown 31 33%
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 27 June 2017.
All research outputs
#16,078,794
of 24,464,848 outputs
Outputs from Frontiers in Microbiology
#15,615
of 27,725 outputs
Outputs of similar age
#193,973
of 321,359 outputs
Outputs of similar age from Frontiers in Microbiology
#336
of 522 outputs
Altmetric has tracked 24,464,848 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 27,725 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 321,359 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 522 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.