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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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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.

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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%