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Noise and Epigenetic Inheritance of Single-Cell Division Times Influence Population Fitness

Overview of attention for article published in Current Biology, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Average Attention Score compared to outputs of the same age and source

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224 Mendeley
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1 CiteULike
Title
Noise and Epigenetic Inheritance of Single-Cell Division Times Influence Population Fitness
Published in
Current Biology, April 2016
DOI 10.1016/j.cub.2016.03.010
Pubmed ID
Authors

Bram Cerulus, Aaron M. New, Ksenia Pougach, Kevin J. Verstrepen

Abstract

The fitness effect of biological noise remains unclear. For example, even within clonal microbial populations, individual cells grow at different speeds. Although it is known that the individuals' mean growth speed can affect population-level fitness, it is unclear how or whether growth speed heterogeneity itself is subject to natural selection. Here, we show that noisy single-cell division times can significantly affect population-level growth rate. Using time-lapse microscopy to measure the division times of thousands of individual S. cerevisiae cells across different genetic and environmental backgrounds, we find that the length of individual cells' division times can vary substantially between clonal individuals and that sublineages often show epigenetic inheritance of division times. By combining these experimental measurements with mathematical modeling, we find that, for a given mean division time, increasing heterogeneity and epigenetic inheritance of division times increases the population growth rate. Furthermore, we demonstrate that the heterogeneity and epigenetic inheritance of single-cell division times can be linked with variation in the expression of catabolic genes. Taken together, our results reveal how a change in noisy single-cell behaviors can directly influence fitness through dynamics that operate independently of effects caused by changes to the mean. These results not only allow a better understanding of microbial fitness but also help to more accurately predict fitness in other clonal populations, such as tumors.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 224 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
France 2 <1%
Hungary 1 <1%
Switzerland 1 <1%
Belgium 1 <1%
Taiwan 1 <1%
Unknown 215 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 60 27%
Researcher 49 22%
Student > Master 21 9%
Student > Bachelor 16 7%
Professor > Associate Professor 12 5%
Other 38 17%
Unknown 28 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 85 38%
Biochemistry, Genetics and Molecular Biology 63 28%
Physics and Astronomy 10 4%
Engineering 8 4%
Mathematics 5 2%
Other 19 8%
Unknown 34 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 26 March 2018.
All research outputs
#4,191,334
of 25,371,288 outputs
Outputs from Current Biology
#6,883
of 14,673 outputs
Outputs of similar age
#62,329
of 315,515 outputs
Outputs of similar age from Current Biology
#121
of 198 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,673 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 61.9. This one has gotten more attention than average, scoring higher than 53% 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 315,515 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 198 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.