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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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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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 173 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 164 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 54 31%
Student > Master 29 17%
Researcher 21 12%
Student > Doctoral Student 12 7%
Professor 9 5%
Other 22 13%
Unknown 26 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 26%
Biochemistry, Genetics and Molecular Biology 26 15%
Physics and Astronomy 18 10%
Immunology and Microbiology 12 7%
Engineering 11 6%
Other 28 16%
Unknown 33 19%
Attention Score in Context

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
#20,291,881
of 22,828,180 outputs
Outputs from BMC Systems Biology
#1,009
of 1,142 outputs
Outputs of similar age
#205,634
of 245,084 outputs
Outputs of similar age from BMC Systems Biology
#26
of 29 outputs
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So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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