Noisy Cell-Size-Correlated Expression of Cyclin B Drives Probabilistic Cell-Size Homeostasis in Fission Yeast

Patterson, James O.; Rees, Paul; Nurse, Paul

doi:10.1016/j.cub.2019.03.011

Cited by 46 publications

(74 citation statements)

References 41 publications

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“…Here, our assumption would be that the formation of this ring has a rate proportional to the size of the bacteria. The dependence on size has been suggested by previous observations [18, 19].…”

Section: Discussionsupporting

confidence: 63%

Efficient computation of stochastic cell-size transient dynamics

et al. 2019

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BackgroundHow small, fast-growing bacteria ensure tight cell-size distributions remains elusive. High-throughput measurement techniques have propelled efforts to build modeling tools that help to shed light on the relationships between cell size, growth and cycle progression. Most proposed models describe cell division as a discrete map between size at birth and size at division with stochastic fluctuations assumed. However, such models underestimate the role of cell size transient dynamics by excluding them.ResultsWe propose an efficient approach for estimation of cell size transient dynamics. Our technique approximates the transient size distribution and statistical moment dynamics of exponential growing cells following an adder strategy with arbitrary precision.ConclusionsWe approximate, up to arbitrary precision, the distribution of division times and size across time for the adder strategy in rod-shaped bacteria cells. Our approach is able to compute statistical moments like mean size and its variance from such distributions efficiently, showing close match with numerical simulations. Additionally, we observed that these distributions have periodic properties. Our approach further might shed light on the mechanisms behind gene product homeostasis.

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Section: Discussionsupporting

confidence: 63%

Efficient computation of stochastic cell-size transient dynamics

et al. 2019

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“…Compared to simple probabilistic sizer models for which cells divide according to a probability of division as a function of cell size ( 12 , 22 ), our equation describes the distribution of sizes at division as a combination of well-defined sources of error. The same holds for the other CVs:

and

…”

Section: Resultsmentioning

confidence: 99%

Reassessment of the Basis of Cell Size Control Based on Analysis of Cell-to-Cell Variability

Facchetti

Knapp

Chang

et al. 2019

Biophysical Journal

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Image acquisition and analysisAll images analysed here are taken from our previous publication [1]. High resolution images were used to obtain cell segmentation at different resolutions by binning pixels (Figs. 2,3, S1). This allowed us to study the effect of the segmentation error. In these cases, we applied the following new semi-automated algorithm to the images acquired at the best z-plane. We first drew manually an approximate cell axis that connected the two cell tips (A and B, see Fig. S7A). The AB distance was a first estimation L of the cell length. A first estimation of the cell radius was calculated as follows. From the middle point M of the AB segment, we derived an intensity profile along the direction orthogonal to the axis (towards both lateral borders of the cell, red dashed line in Fig. S7A). The steepest gradient of this signal identified the border of the cell, i.e. the cell radius. We repeated this gradient procedure using neighbouring points of M (at a distance k·dx, with k=-3, -2, … , +2, +3, and where dx is the pixel size). The average of all these values gave our first estimation of the radius. We then shortened the segment AB by this amount from both ends. This defined the new segment A'B'. We divided this segment into n equal parts (n=0.5·L/dx) by placing n-1 internal points. The gradient procedure we used for the middle point M was then applied to all these points and to the two extremal points A' and B'. This identified the lateral borders of the cells. The symmetry axis of the resulting lateral borders was taken to be the new symmetry axis of the cell (segment CD). From both extreme points C and D, we derived the intensity profile along the different radial directions (from 0 to 180 degrees, steps of 2 degrees, purple dashed line in Fig. S7B). Ideally, the distance of the cell border to the CD segment should always have been equal to R for every point from C to D. However, cell irregularity and imaging defects altered this width. Therefore, after calculating the width from a point xi, if the difference between this width and the width from the previous point xi-1 was bigger than a given threshold (0.1 μm), we set the width equal to the width from xi-1. The final result was a set of points that described the cell border. From these points we derived the cell length as the maximal distance between two points of the set (Fig. S7C). The cell radius was defined as the average of its value at different positions along the CD segment, i.e. excluding the two cell tips (Fig. S7C). Surface area and volume were then calculated using simple geometrical equations. As

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“…The tyrosine phosphatase Cdc25, which dephosphorylates and activates CDK, has been proposed as such an unstable activator ( Keifenheim et al, 2017 ). Similarly, the levels of mitotic cyclin B Cdc13 have been shown to scale with cell size and impact on the likelihood of cell division ( Patterson et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of mutants with increased variation in cell size at onset of mitosis in fission yeast

Scotchman

Kume

Navarro

et al. 2021

Journal of Cell Science

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Fission yeast cells divide at a similar cell length with little variation about the mean. This is thought to be the result of a control mechanism that senses size and corrects for any deviations by advancing or delaying onset of mitosis. Gene deletions that advance cells into mitosis at a smaller size or delay cells entering mitosis, have identified genes potentially involved in this mechanism. However, the molecular basis of this control is still not understood. In this work, we have screened for genes, which when deleted, increase the variability in size of dividing cells. The strongest candidate of this screen was mga2. The mga2 deletion shows a greater variation in cell length at division, with a coefficient of variation (CV) of 15-24% while the wild type strain has a CV of 5-8%. Furthermore, unlike wild type cells, the mga2 deletion cells are unable to correct cell size deviations within one cell cycle. We show that the mga2 gene genetically interacts with nem1 and influences the nuclear membrane, and speculate that it may influence the nucleus/cytoplasmic transport of CDK regulators.

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Noisy Cell-Size-Correlated Expression of Cyclin B Drives Probabilistic Cell-Size Homeostasis in Fission Yeast

Cited by 46 publications

References 41 publications

Efficient computation of stochastic cell-size transient dynamics

Efficient computation of stochastic cell-size transient dynamics

Reassessment of the Basis of Cell Size Control Based on Analysis of Cell-to-Cell Variability

Identification of mutants with increased variation in cell size at onset of mitosis in fission yeast

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