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Prediction of Phenotypic Antimicrobial Resistance Profiles From Whole Genome Sequences of Non-typhoidal Salmonella enterica

Overview of attention for article published in Frontiers in Microbiology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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Title
Prediction of Phenotypic Antimicrobial Resistance Profiles From Whole Genome Sequences of Non-typhoidal Salmonella enterica
Published in
Frontiers in Microbiology, March 2018
DOI 10.3389/fmicb.2018.00592
Pubmed ID
Authors

Saskia Neuert, Satheesh Nair, Martin R. Day, Michel Doumith, Philip M. Ashton, Kate C. Mellor, Claire Jenkins, Katie L. Hopkins, Neil Woodford, Elizabeth de Pinna, Gauri Godbole, Timothy J. Dallman

Abstract

Surveillance of antimicrobial resistance (AMR) in non-typhoidal Salmonella enterica (NTS), is essential for monitoring transmission of resistance from the food chain to humans, and for establishing effective treatment protocols. We evaluated the prediction of phenotypic resistance in NTS from genotypic profiles derived from whole genome sequencing (WGS). Genes and chromosomal mutations responsible for phenotypic resistance were sought in WGS data from 3,491 NTS isolates received by Public Health England's Gastrointestinal Bacteria Reference Unit between April 2014 and March 2015. Inferred genotypic AMR profiles were compared with phenotypic susceptibilities determined for fifteen antimicrobials using EUCAST guidelines. Discrepancies between phenotypic and genotypic profiles for one or more antimicrobials were detected for 76 isolates (2.18%) although only 88/52,365 (0.17%) isolate/antimicrobial combinations were discordant. Of the discrepant results, the largest number were associated with streptomycin (67.05%, n = 59). Pan-susceptibility was observed in 2,190 isolates (62.73%). Overall, resistance to tetracyclines was most common (26.27% of isolates, n = 917) followed by sulphonamides (23.72%, n = 828) and ampicillin (21.43%, n = 748). Multidrug resistance (MDR), i.e., resistance to three or more antimicrobial classes, was detected in 848 isolates (24.29%) with resistance to ampicillin, streptomycin, sulphonamides and tetracyclines being the most common MDR profile (n = 231; 27.24%). For isolates with this profile, all but one were S. Typhimurium and 94.81% (n = 219) had the resistance determinants blaTEM-1,strA-strB, sul2 and tet(A). Extended-spectrum β-lactamase genes were identified in 41 isolates (1.17%) and multiple mutations in chromosomal genes associated with ciprofloxacin resistance in 82 isolates (2.35%). This study showed that WGS is suitable as a rapid means of determining AMR patterns of NTS for public health surveillance.

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The data shown below were collected from the profiles of 12 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 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 169 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 18%
Researcher 23 14%
Student > Master 20 12%
Student > Postgraduate 12 7%
Student > Doctoral Student 8 5%
Other 26 15%
Unknown 49 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 14%
Biochemistry, Genetics and Molecular Biology 23 14%
Immunology and Microbiology 22 13%
Veterinary Science and Veterinary Medicine 13 8%
Medicine and Dentistry 11 7%
Other 15 9%
Unknown 61 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 30 January 2019.
All research outputs
#3,487,390
of 24,464,848 outputs
Outputs from Frontiers in Microbiology
#3,167
of 27,725 outputs
Outputs of similar age
#68,447
of 334,286 outputs
Outputs of similar age from Frontiers in Microbiology
#118
of 594 outputs
Altmetric has tracked 24,464,848 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
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 has done well, scoring higher than 88% 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 334,286 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 594 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.