4.8 Article

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

期刊

CURRENT BIOLOGY
卷 26, 期 9, 页码 1138-1147

出版社

CELL PRESS
DOI: 10.1016/j.cub.2016.03.010

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资金

  1. Research Foundation Flanders (FWO-Vlaanderen)
  2. AB-InBev Baillet-Latour Foundation
  3. Marie Curie Actions
  4. EMBO [ALTF-505-2014]
  5. Belgian Federal Science Policy Office
  6. European Union (ERC) [CoG682009]
  7. HFSP [RGP0050/2013]
  8. KU Leuven NATAR Program
  9. VIB
  10. EMBO YIP program
  11. FWO
  12. IWT

向作者/读者索取更多资源

The fitness effect of biological noise remains unclear. For example, even within clonal microbial populations, individual cells grow at different speeds. Although it is knownthat 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 subline-ages 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.

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