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Enrichment allows identification of diverse, rare elements in metagenomic resistome-virulome sequencing

Overview of attention for article published in Microbiome, October 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 blog
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16 X users

Citations

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60 Dimensions

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131 Mendeley
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Title
Enrichment allows identification of diverse, rare elements in metagenomic resistome-virulome sequencing
Published in
Microbiome, October 2017
DOI 10.1186/s40168-017-0361-8
Pubmed ID
Authors

Noelle R. Noyes, Maggie E. Weinroth, Jennifer K. Parker, Chris J. Dean, Steven M. Lakin, Robert A. Raymond, Pablo Rovira, Enrique Doster, Zaid Abdo, Jennifer N. Martin, Kenneth L. Jones, Jaime Ruiz, Christina A. Boucher, Keith E. Belk, Paul S. Morley

Abstract

Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to limitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias. The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins. These results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistome-virulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of microbiome-resistome dynamics.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 131 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 21%
Student > Ph. D. Student 20 15%
Student > Master 16 12%
Student > Bachelor 9 7%
Student > Doctoral Student 7 5%
Other 22 17%
Unknown 29 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 21%
Biochemistry, Genetics and Molecular Biology 23 18%
Medicine and Dentistry 9 7%
Immunology and Microbiology 8 6%
Computer Science 6 5%
Other 22 17%
Unknown 36 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 14 June 2018.
All research outputs
#2,361,583
of 25,711,518 outputs
Outputs from Microbiome
#943
of 1,790 outputs
Outputs of similar age
#44,418
of 336,943 outputs
Outputs of similar age from Microbiome
#25
of 45 outputs
Altmetric has tracked 25,711,518 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,790 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.9. This one is in the 47th percentile – i.e., 47% 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 336,943 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 86% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.