Cell Length Growth in the Fission Yeast Cell Cycle: Is It (Bi)linear or (Bi)exponential?

Pesti, Benedek; Nagy, Zsófia; Papp, László; Sipiczki, Matthias; Sveiczer, Ákos

doi:10.3390/pr9091533

Cited by 2 publications

(2 citation statements)

References 49 publications

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“…Therefore, the results of this section apply to cells obeying more complex growth laws than in the previous section. For example, fission yeasts have been observed to follow piecewise growing patterns [40,41], either bi-linear or biexponential during the elongation phase. Also, Corynebacterium glutamicum exhibits asymptotically linear growth [42], unlike most bacteria.…”

Section: Asymptotic Behaviour For General Partitioning Kernelmentioning

confidence: 99%

Analytical cell size distribution: lineage-population bias and parameter inference

Genthon

2022

J. R. Soc. Interface.

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We derive analytical steady-state cell size distributions for size-controlled cells in single-lineage experiments, such as the mother machine, which are fundamentally different from batch cultures where populations of cells grow freely. For exponential single-cell growth, characterizing most bacteria, the lineage-population bias is obtained explicitly. In addition, if volume is evenly split between the daughter cells at division, we show that cells are on average smaller in populations than in lineages. For more general power-law growth rates and deterministic volume partitioning, both symmetric and asymmetric, we derive the exact lineage distribution. This solution is in good agreement with Escherichia coli mother machine data and can be used to infer cell cycle parameters such as the strength of the size control and the asymmetry of the division. When introducing stochastic volume partitioning, we derive the large-size and small-size tails of the lineage distribution and show that the lineage-population bias only depends on the single-cell growth rate. These asymptotic behaviours are extended to the adder model of cell size control. When considering noisy single-cell growth rate, we derive the large-size lineage and population distributions. Finally, we show that introducing noise, either on the volume partitioning or on the single-cell growth rate, can cancel the lineage-population bias.

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Section: Asymptotic Behaviour For General Partitioning Kernelmentioning

confidence: 99%

Analytical cell size distribution: lineage-population bias and parameter inference

Genthon

2022

J. R. Soc. Interface.

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show abstract

“…Therefore, the following results apply to cells obeying more complex growth laws than in the previous section. For example, fission yeasts have been observed to follow piece-wise growing patterns [34,35], either bi-linear or bi-exponential during the elongation phase. The bacterium Corynebacterium glutamicum exhibits asymptotically linear growth [36], unlike most bacteria.…”

Section: Asymptotic Behavior For General Partitioning Kernelmentioning

confidence: 99%

Analytical cell size distribution: lineage-population bias and parameter inference

Genthon¹

2022

Preprint

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Solving population balance equations, we derive analytical steady-state cell size distributions for single-lineage experiments, such as the mother machine. These experiments are fundamentally different from batch cultures where populations of cells grow freely, and the statistical bias between them is obtained by comparing our results to cell size distributions measured in population. For exponential single-cell growth, characterizing most bacteria, the lineage-population bias is obtained explicitly. In addition, if volume is evenly split between the daughter cells at division, we show that cells are on average smaller in populations. For more general power-law growth rates and deterministic volume partitioning, both symmetric and asymmetric, we derive the exact lineage distribution. This solution is in good agreement with E. Coli mother machine data, and can be used to infer cell cycle parameters, such as the strength of the size control and the asymmetry of the division. When introducing stochastic volume partitioning, we derive the large-size and smallsize tails of the lineage size distributions, and show that they respectively do not depend on the partitioning of volume and on the size control strength. Finally, we show that introducing noise, either on the volume partitioning or on the single cell growth rate, can cancel the lineage-population bias.

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Cell Length Growth in the Fission Yeast Cell Cycle: Is It (Bi)linear or (Bi)exponential?

Cited by 2 publications

References 49 publications

Analytical cell size distribution: lineage-population bias and parameter inference

Analytical cell size distribution: lineage-population bias and parameter inference

Analytical cell size distribution: lineage-population bias and parameter inference

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