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Why do bacteria regulate public goods by quorum sensing?—How the shapes of cost and benefit functions determine the form of optimal regulation

Overview of attention for article published in Frontiers in Microbiology, July 2015
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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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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2 news outlets
blogs
1 blog
twitter
12 X users

Citations

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66 Dimensions

Readers on

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112 Mendeley
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Title
Why do bacteria regulate public goods by quorum sensing?—How the shapes of cost and benefit functions determine the form of optimal regulation
Published in
Frontiers in Microbiology, July 2015
DOI 10.3389/fmicb.2015.00767
Pubmed ID
Authors

Silja Heilmann, Sandeep Krishna, Benjamin Kerr

Abstract

Many bacteria secrete compounds which act as public goods. Such compounds are often under quorum sensing (QS) regulation, yet it is not understood exactly when bacteria may gain from having a public good under QS regulation. Here, we show that the optimal public good production rate per cell as a function of population size (the optimal production curve, OPC) depends crucially on the cost and benefit functions of the public good and that the OPC will fall into one of two categories: Either it is continuous or it jumps from zero discontinuously at a critical population size. If, e.g., the public good has accelerating returns and linear cost, then the OPC is discontinuous and the best strategy thus to ramp up production sharply at a precise population size. By using the example of public goods with accelerating and diminishing returns (and linear cost) we are able to determine how the two different categories of OPSs can best be matched by production regulated through a QS signal feeding back on its own production. We find that the optimal QS parameters are different for the two categories and specifically that public goods which provide accelerating returns, call for stronger positive signal feedback.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
India 1 <1%
France 1 <1%
Unknown 109 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 33%
Researcher 15 13%
Student > Master 15 13%
Student > Bachelor 11 10%
Student > Doctoral Student 8 7%
Other 12 11%
Unknown 14 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 32%
Biochemistry, Genetics and Molecular Biology 24 21%
Immunology and Microbiology 11 10%
Environmental Science 5 4%
Chemical Engineering 4 4%
Other 15 13%
Unknown 17 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 30 November 2022.
All research outputs
#1,244,534
of 24,129,125 outputs
Outputs from Frontiers in Microbiology
#717
of 27,173 outputs
Outputs of similar age
#16,241
of 267,524 outputs
Outputs of similar age from Frontiers in Microbiology
#12
of 363 outputs
Altmetric has tracked 24,129,125 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 27,173 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 done particularly well, scoring higher than 97% 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 267,524 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 93% of its contemporaries.
We're also able to compare this research output to 363 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.