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Models of microbiome evolution incorporating host and microbial selection

Overview of attention for article published in Microbiome, September 2017
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
1 blog
twitter
39 tweeters

Citations

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20 Dimensions

Readers on

mendeley
140 Mendeley
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Title
Models of microbiome evolution incorporating host and microbial selection
Published in
Microbiome, September 2017
DOI 10.1186/s40168-017-0343-x
Pubmed ID
Authors

Qinglong Zeng, Steven Wu, Jeet Sukumaran, Allen Rodrigo

Abstract

Numerous empirical studies suggest that hosts and microbes exert reciprocal selective effects on their ecological partners. Nonetheless, we still lack an explicit framework to model the dynamics of both hosts and microbes under selection. In a previous study, we developed an agent-based forward-time computational framework to simulate the neutral evolution of host-associated microbial communities in a constant-sized, unstructured population of hosts. These neutral models allowed offspring to sample microbes randomly from parents and/or from the environment. Additionally, the environmental pool of available microbes was constituted by fixed and persistent microbial OTUs and by contributions from host individuals in the preceding generation. In this paper, we extend our neutral models to allow selection to operate on both hosts and microbes. We do this by constructing a phenome for each microbial OTU consisting of a sample of traits that influence host and microbial fitnesses independently. Microbial traits can influence the fitness of hosts ("host selection") and the fitness of microbes ("trait-mediated microbial selection"). Additionally, the fitness effects of traits on microbes can be modified by their hosts ("host-mediated microbial selection"). We simulate the effects of these three types of selection, individually or in combination, on microbiome diversities and the fitnesses of hosts and microbes over several thousand generations of hosts. We show that microbiome diversity is strongly influenced by selection acting on microbes. Selection acting on hosts only influences microbiome diversity when there is near-complete direct or indirect parental contribution to the microbiomes of offspring. Unsurprisingly, microbial fitness increases under microbial selection. Interestingly, when host selection operates, host fitness only increases under two conditions: (1) when there is a strong parental contribution to microbial communities or (2) in the absence of a strong parental contribution, when host-mediated selection acts on microbes concomitantly. We present a computational framework that integrates different selective processes acting on the evolution of microbiomes. Our framework demonstrates that selection acting on microbes can have a strong effect on microbial diversities and fitnesses, whereas selection on hosts can have weaker outcomes.

Twitter Demographics

The data shown below were collected from the profiles of 39 tweeters 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 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 140 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 29%
Student > Ph. D. Student 31 22%
Student > Master 19 14%
Student > Bachelor 8 6%
Student > Doctoral Student 5 4%
Other 17 12%
Unknown 19 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 62 44%
Biochemistry, Genetics and Molecular Biology 22 16%
Immunology and Microbiology 9 6%
Environmental Science 7 5%
Engineering 3 2%
Other 10 7%
Unknown 27 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 24 May 2018.
All research outputs
#935,628
of 18,035,775 outputs
Outputs from Microbiome
#313
of 1,094 outputs
Outputs of similar age
#23,968
of 286,366 outputs
Outputs of similar age from Microbiome
#1
of 7 outputs
Altmetric has tracked 18,035,775 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,094 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.7. This one has gotten more attention than average, scoring higher than 71% 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 286,366 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them