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Bacterial social interactions drive the emergence of differential spatial colony structures

Overview of attention for article published in BMC Systems Biology, September 2015
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1 tweeter

Citations

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33 Dimensions

Readers on

mendeley
134 Mendeley
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3 CiteULike
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Title
Bacterial social interactions drive the emergence of differential spatial colony structures
Published in
BMC Systems Biology, September 2015
DOI 10.1186/s12918-015-0188-5
Pubmed ID
Authors

Andrew E. Blanchard, Ting Lu

Abstract

Social interactions have been increasingly recognized as one of the major factors that contribute to the dynamics and function of bacterial communities. To understand their functional roles and enable the design of robust synthetic consortia, one fundamental step is to determine the relationship between the social interactions of individuals and the spatiotemporal structures of communities. We present a systematic computational survey on this relationship for two-species communities by developing and utilizing a hybrid computational framework that combines discrete element techniques with reaction-diffusion equations. We found that deleterious interactions cause an increased variance in relative abundance, a drastic decrease in surviving lineages, and a rough expanding front. In contrast, beneficial interactions contribute to a reduced variance in relative abundance, an enhancement in lineage number, and a smooth expanding front. We also found that mutualism promotes spatial homogeneity and population robustness while competition increases spatial segregation and population fluctuations. To examine the generality of these findings, a large set of initial conditions with varying density and species abundance was tested and analyzed. In addition, a simplified mathematical model was developed to provide an analytical interpretation of the findings. This work advances our fundamental understanding of bacterial social interactions and population structures and, simultaneously, benefits synthetic biology for facilitated engineering of artificial microbial consortia.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 3 2%
Germany 2 1%
France 1 <1%
United Kingdom 1 <1%
Belgium 1 <1%
Spain 1 <1%
Unknown 125 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 35%
Student > Master 23 17%
Researcher 16 12%
Student > Doctoral Student 7 5%
Student > Bachelor 7 5%
Other 22 16%
Unknown 12 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 32%
Biochemistry, Genetics and Molecular Biology 20 15%
Physics and Astronomy 11 8%
Immunology and Microbiology 10 7%
Engineering 9 7%
Other 23 17%
Unknown 18 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 18 September 2015.
All research outputs
#5,422,186
of 6,364,199 outputs
Outputs from BMC Systems Biology
#685
of 772 outputs
Outputs of similar age
#158,871
of 198,837 outputs
Outputs of similar age from BMC Systems Biology
#26
of 29 outputs
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