↓ Skip to main content

Intestinal microbial communities associated with acute enteric infections and disease recovery

Overview of attention for article published in Microbiome, September 2015
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#48 of 384)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

news
4 news outlets
blogs
2 blogs
twitter
19 tweeters

Readers on

mendeley
70 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Intestinal microbial communities associated with acute enteric infections and disease recovery
Published in
Microbiome, September 2015
DOI 10.1186/s40168-015-0109-2
Pubmed ID
Authors

Pallavi Singh, Tracy K Teal, Terence L Marsh, James M Tiedje, Rebekah Mosci, Katherine Jernigan, Angela Zell, Duane W Newton, Hossein Salimnia, Paul Lephart, Daniel Sundin, Walid Khalife, Robert A Britton, James T Rudrik, Shannon D Manning, Tracy K. Teal, Terence L. Marsh, James M. Tiedje, Duane W. Newton, Robert A. Britton, James T. Rudrik, Shannon D. Manning

Abstract

The intestinal microbiome represents a complex network of microbes that are important for human health and preventing pathogen invasion. Studies that examine differences in intestinal microbial communities across individuals with and without enteric infections are useful for identifying microbes that support or impede intestinal health. 16S rRNA gene sequencing was conducted on stool DNA from patients with enteric infections (n = 200) and 75 healthy family members to identify differences in intestinal community composition. Stools from 13 patients were also examined post-infection to better understand how intestinal communities recover. Patient communities had lower species richness, evenness, and diversity versus uninfected communities, while principle coordinate analysis demonstrated close clustering of uninfected communities, but not the patient communities, irrespective of age, gender, and race. Differences in community composition between patients and family members were mostly due to variation in the abundance of phyla Proteobacteria, Bacteroidetes, and Firmicutes. Patient communities had significantly more Proteobacteria representing genus Escherichia relative to uninfected communities, which were dominated by Bacteroides. Intestinal communities from patients with bloody diarrhea clustered together in the neighbor-joining phylogeny, while communities from 13 patients' post-infection had a significant increase in Bacteroidetes and Firmicutes and clustered together with uninfected communities. These data demonstrate that the intestinal communities in patients with enteric bacterial infections get altered in similar ways. Furthermore, preventing an increase in Escherichia abundance may be an important consideration for future prevention strategies.

Twitter Demographics

The data shown below were collected from the profiles of 19 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 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
New Zealand 1 1%
Unknown 66 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 26%
Student > Bachelor 12 17%
Researcher 12 17%
Student > Master 10 14%
Unspecified 5 7%
Other 13 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 50%
Medicine and Dentistry 7 10%
Unspecified 6 9%
Immunology and Microbiology 5 7%
Biochemistry, Genetics and Molecular Biology 3 4%
Other 14 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 54. 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 06 May 2016.
All research outputs
#193,366
of 8,760,756 outputs
Outputs from Microbiome
#48
of 384 outputs
Outputs of similar age
#8,522
of 239,182 outputs
Outputs of similar age from Microbiome
#2
of 19 outputs
Altmetric has tracked 8,760,756 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 384 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 41.8. This one has done well, scoring higher than 87% 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 239,182 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.