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Antagonistic interactions are sufficient to explain self-assemblage of bacterial communities in a homogeneous environment: a computational modeling approach

Overview of attention for article published in Frontiers in Microbiology, May 2015
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Title
Antagonistic interactions are sufficient to explain self-assemblage of bacterial communities in a homogeneous environment: a computational modeling approach
Published in
Frontiers in Microbiology, May 2015
DOI 10.3389/fmicb.2015.00489
Pubmed ID
Authors

Román Zapién-Campos, Gabriela Olmedo-Álvarez, Moisés Santillán

Abstract

Most of the studies in Ecology have been devoted to analyzing the effects the environment has on individuals, populations, and communities, thus neglecting the effects of biotic interactions on the system dynamics. In the present work we study the structure of bacterial communities in the oligotrophic shallow water system of Churince, Cuatro Cienegas, Mexico. Since the physicochemical conditions of this water system are homogeneous and quite stable in time, it is an excellent candidate to study how biotic factors influence the structure of bacterial communities. In a previous study, the binary antagonistic interactions of 78 bacterial strains, isolated from Churince, were experimentally determined. We employ these data to develop a computer algorithm to simulate growth experiments in a cellular grid representing the pond. Remarkably, in our model, the dynamics of all the simulated bacterial populations is determined solely by antagonistic interactions. Our results indicate that all bacterial strains (even those that are antagonized by many other bacteria) survive in the long term, and that the underlying mechanism is the formation of bacterial community patches. Patches corresponding to less antagonistic and highly susceptible strains are consistently isolated from the highly-antagonistic bacterial colonies by patches of neutral strains. These results concur with the observed features of the bacterial community structure previously reported. Finally, we study how our findings depend on factors like initial population size, differential population growth rates, homogeneous population death rates, and enhanced bacterial diffusion.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 2 3%
United States 1 2%
Unknown 59 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 19%
Student > Bachelor 11 18%
Student > Master 10 16%
Researcher 9 15%
Student > Doctoral Student 5 8%
Other 9 15%
Unknown 6 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 35%
Biochemistry, Genetics and Molecular Biology 10 16%
Environmental Science 9 15%
Mathematics 2 3%
Chemistry 2 3%
Other 7 11%
Unknown 10 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 21 May 2015.
All research outputs
#7,517,625
of 24,885,505 outputs
Outputs from Frontiers in Microbiology
#7,509
of 28,434 outputs
Outputs of similar age
#82,566
of 271,826 outputs
Outputs of similar age from Frontiers in Microbiology
#95
of 393 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 28,434 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has gotten more attention than average, scoring higher than 73% 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 271,826 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 393 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.