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Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture

Overview of attention for article published in Science of the Total Environment, September 2016
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  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

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7 tweeters

Citations

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16 Dimensions

Readers on

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47 Mendeley
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Title
Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture
Published in
Science of the Total Environment, September 2016
DOI 10.1016/j.scitotenv.2016.04.087
Pubmed ID
Authors

Sheridan K. Haack, Joseph W. Duris, Dana W. Kolpin, Michael J. Focazio, Michael T. Meyer, Heather E. Johnson, Ryan J. Oster, William T. Foreman

Abstract

Animal waste, stream water, and streambed sediment from 19 small (<32km(2)) watersheds in 12U.S. states having either no major animal agriculture (control, n=4), or predominantly beef (n=4), dairy (n=3), swine (n=5), or poultry (n=3) were tested for: 1) cholesterol, coprostanol, estrone, and fecal indicator bacteria (FIB) concentrations, and 2) shiga-toxin producing and enterotoxigenic Escherichia coli, Salmonella, Campylobacter, and pathogenic and vancomycin-resistant enterococci by polymerase chain reaction (PCR) on enrichments, and/or direct quantitative PCR. Pathogen genes were most frequently detected in dairy wastes, followed by beef, swine and poultry wastes in that order; there was only one detection of an animal-source-specific pathogen gene (stx1) in any water or sediment sample in any control watershed. Post-rainfall pathogen gene numbers in stream water were significantly correlated with FIB, cholesterol and coprostanol concentrations, and were most highly correlated in dairy watershed samples collected from 3 different states. Although collected across multiple states and ecoregions, animal-waste gene profiles were distinctive via discriminant analysis. Stream water gene profiles could also be discriminated by the watershed animal type. Although pathogen genes were not abundant in stream water or streambed samples, PCR on enrichments indicated that many genes were from viable organisms, including several (shiga-toxin producing or enterotoxigenic E. coli, Salmonella, vancomycin-resistant enterococci) that could potentially affect either human or animal health. Pathogen gene numbers and types in stream water samples were influenced most by animal type, by local factors such as whether animals had stream access, and by the amount of local rainfall, and not by studied watershed soil or physical characteristics. Our results indicated that stream water in small agricultural U.S. watersheds was susceptible to pathogen gene inputs under typical agricultural practices and environmental conditions. Pathogen gene profiles may offer the potential to address both source of, and risks associated with, fecal pollution.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 2%
United States 1 2%
Unknown 45 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 23%
Student > Ph. D. Student 7 15%
Student > Master 5 11%
Student > Bachelor 5 11%
Student > Doctoral Student 3 6%
Other 8 17%
Unknown 8 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 19%
Environmental Science 7 15%
Immunology and Microbiology 6 13%
Biochemistry, Genetics and Molecular Biology 5 11%
Veterinary Science and Veterinary Medicine 3 6%
Other 7 15%
Unknown 10 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 13 May 2016.
All research outputs
#3,887,740
of 15,557,767 outputs
Outputs from Science of the Total Environment
#3,824
of 14,355 outputs
Outputs of similar age
#69,966
of 265,742 outputs
Outputs of similar age from Science of the Total Environment
#47
of 172 outputs
Altmetric has tracked 15,557,767 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 14,355 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has gotten more attention than average, scoring higher than 73% 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 265,742 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 172 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 72% of its contemporaries.