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Towards diagnostic metagenomics of Campylobacter in fecal samples

Overview of attention for article published in BMC Microbiology, June 2017
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  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

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4 tweeters

Citations

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10 Dimensions

Readers on

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46 Mendeley
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Title
Towards diagnostic metagenomics of Campylobacter in fecal samples
Published in
BMC Microbiology, June 2017
DOI 10.1186/s12866-017-1041-3
Pubmed ID
Authors

Sandra Christine Andersen, Kristoffer Kiil, Christoffer Bugge Harder, Mathilde Hasseldam Josefsen, Søren Persson, Eva Møller Nielsen, Jeffrey Hoorfar

Abstract

The development of diagnostic metagenomics is driven by the need for universal, culture-independent methods for detection and characterization of pathogens to substitute the time-consuming, organism-specific, and often culture-based laboratory procedures for epidemiological source-tracing. Some of the challenges in diagnostic metagenomics are, that it requires a great next-generation sequencing depth and unautomated data analysis. DNA from human fecal samples spiked with 7.75 × 10(1)-7.75 × 10(7) colony forming unit (CFU)/ml Campylobacter jejuni and chicken fecal samples spiked with 1 × 10(2)-1 × 10(6) CFU/g Campylobacter jejuni was sequenced and data analysis was done by the metagenomic tools Kraken and CLARK. More hits were obtained at higher spiking levels, however with no significant linear correlations (human samples p = 0.12, chicken samples p = 0.10). Therefore, no definite detection limit could be determined, but the lowest spiking levels found positive were 7.75 × 10(4) CFU/ml in human feces and 10(3) CFU/g in chicken feces. Eight human clinical fecal samples with estimated Campylobacter infection loads from 9.2 × 10(4)-1.0 × 10(9) CFU/ml were analyzed using the same methods. It was possible to detect Campylobacter in all the clinical samples. Sensitivity in diagnostic metagenomics is improving and has reached a clinically relevant level. There are still challenges to overcome before real-time diagnostic metagenomics can replace quantitative polymerase chain reaction (qPCR) or culture-based surveillance and diagnostics, but it is a promising new technology.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 26%
Student > Ph. D. Student 5 11%
Student > Bachelor 4 9%
Student > Master 4 9%
Other 2 4%
Other 5 11%
Unknown 14 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 24%
Biochemistry, Genetics and Molecular Biology 6 13%
Veterinary Science and Veterinary Medicine 3 7%
Computer Science 3 7%
Immunology and Microbiology 3 7%
Other 4 9%
Unknown 16 35%

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 05 September 2017.
All research outputs
#6,997,822
of 11,707,803 outputs
Outputs from BMC Microbiology
#834
of 1,650 outputs
Outputs of similar age
#141,101
of 271,751 outputs
Outputs of similar age from BMC Microbiology
#23
of 52 outputs
Altmetric has tracked 11,707,803 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,650 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% 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 271,751 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.