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Social Interaction, Noise and Antibiotic-Mediated Switches in the Intestinal Microbiota

Overview of attention for article published in PLoS Computational Biology, April 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

twitter
9 X users
peer_reviews
1 peer review site
facebook
1 Facebook page

Citations

dimensions_citation
54 Dimensions

Readers on

mendeley
218 Mendeley
citeulike
2 CiteULike
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Title
Social Interaction, Noise and Antibiotic-Mediated Switches in the Intestinal Microbiota
Published in
PLoS Computational Biology, April 2012
DOI 10.1371/journal.pcbi.1002497
Pubmed ID
Authors

Vanni Bucci, Serena Bradde, Giulio Biroli, Joao B. Xavier

Abstract

The intestinal microbiota plays important roles in digestion and resistance against entero-pathogens. As with other ecosystems, its species composition is resilient against small disturbances but strong perturbations such as antibiotics can affect the consortium dramatically. Antibiotic cessation does not necessarily restore pre-treatment conditions and disturbed microbiota are often susceptible to pathogen invasion. Here we propose a mathematical model to explain how antibiotic-mediated switches in the microbiota composition can result from simple social interactions between antibiotic-tolerant and antibiotic-sensitive bacterial groups. We build a two-species (e.g. two functional-groups) model and identify regions of domination by antibiotic-sensitive or antibiotic-tolerant bacteria, as well as a region of multistability where domination by either group is possible. Using a new framework that we derived from statistical physics, we calculate the duration of each microbiota composition state. This is shown to depend on the balance between random fluctuations in the bacterial densities and the strength of microbial interactions. The singular value decomposition of recent metagenomic data confirms our assumption of grouping microbes as antibiotic-tolerant or antibiotic-sensitive in response to a single antibiotic. Our methodology can be extended to multiple bacterial groups and thus it provides an ecological formalism to help interpret the present surge in microbiome data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 218 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 17 8%
Spain 2 <1%
Mexico 2 <1%
Portugal 1 <1%
United Kingdom 1 <1%
Finland 1 <1%
Germany 1 <1%
Sweden 1 <1%
Russia 1 <1%
Other 2 <1%
Unknown 189 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 27%
Student > Ph. D. Student 58 27%
Student > Master 20 9%
Professor 15 7%
Student > Doctoral Student 11 5%
Other 41 19%
Unknown 14 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 95 44%
Biochemistry, Genetics and Molecular Biology 24 11%
Physics and Astronomy 14 6%
Immunology and Microbiology 13 6%
Medicine and Dentistry 12 6%
Other 39 18%
Unknown 21 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 27 July 2020.
All research outputs
#5,315,263
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#4,048
of 8,964 outputs
Outputs of similar age
#34,491
of 175,705 outputs
Outputs of similar age from PLoS Computational Biology
#35
of 100 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 54% 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 175,705 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 80% of its contemporaries.
We're also able to compare this research output to 100 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 65% of its contemporaries.