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

Scotchman, Elizabeth; Kume, Kazunori; Navarro, Francisco J.; Nurse, Paul

doi:10.1242/jcs.251769

Cited by 15 publications

(9 citation statements)

References 57 publications

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“…A slope of −1 for this regression line is indicative of the sizer strategy, while a slope of 0 implies the adder strategy. Such plots have been reported many times in the literature for wild-type haploid cells and generally show a clear negative correlation with a slope between −0.7 and −0.9 [28,36,51,53], while there is also a study showing that the slope can be as low as −0.37 for wild-type diploids [28]. Based on the lineage data, we find that the slope is typically −0.7 for EMM, which is consistent with the values reported in previous studies, while the slope is typically −0.5 for YE.…”

Section: Plos Computational Biologysupporting

confidence: 71%

“…In the study of cell size dynamics, a core issue is to understand the size homeostasis strategies in various cell types, especially in fission yeast [36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51]. There are three popular phenomenological models of cell size control leading to size homeostasis [52]: (i) the timer strategy which implies a constant time between successive divisions regardless of initial size; (ii) the sizer strategy which implies cell division upon attainment of a critical size, and (iii) the adder strategy which implies a constant size addition between consecutive generations.…”

Section: Introductionmentioning

confidence: 99%

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Characterizing non-exponential growth and bimodal cell size distributions in fission yeast: An analytical approach

2022

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Unlike many single-celled organisms, the growth of fission yeast cells within a cell cycle is not exponential. It is rather characterized by three distinct phases (elongation, septation, and reshaping), each with a different growth rate. Experiments also showed that the distribution of cell size in a lineage can be bimodal, unlike the unimodal distributions measured for the bacterium Escherichia coli. Here we construct a detailed stochastic model of cell size dynamics in fission yeast. The theory leads to analytic expressions for the cell size and the birth size distributions, and explains the origin of bimodality seen in experiments. In particular, our theory shows that the left peak in the bimodal distribution is associated with cells in the elongation phase, while the right peak is due to cells in the septation and reshaping phases. We show that the size control strategy, the variability in the added size during a cell cycle, and the fraction of time spent in each of the three cell growth phases have a strong bearing on the shape of the cell size distribution. Furthermore, we infer all the parameters of our model by matching the theoretical cell size and birth size distributions to those from experimental single-cell time-course data for seven different growth conditions. Our method provides a much more accurate means of determining the size control strategy (timer, adder or sizer) than the standard method based on the slope of the best linear fit between the birth and division sizes. We also show that the variability in added size and the strength of size control in fission yeast depend weakly on the temperature but strongly on the culture medium. More importantly, we find that stronger size homeostasis and larger added size variability are required for fission yeast to adapt to unfavorable environmental conditions.

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Section: Plos Computational Biologysupporting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

Characterizing non-exponential growth and bimodal cell size distributions in fission yeast: An analytical approach

2022

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“…This prompted us to investigate whether overexpression of ppk21 + played a role in repairing the defective G2/M transition of the ksg1-208 cells. Fission yeast cells enter into mitosis at a reproducible mean size of 13∼15 μm, and a longer cell length at division indicates the delay of G2/M transition, and vice versa ( Mitchison and Nurse, 1985 ; Scotchman et al, 2021 ). Then we measured the cell length of the ksg1-208 cells at division, and determined the effects of Ppk21 overexpression on the cell length of ksg1-208 cells.…”

Section: Resultsmentioning

confidence: 99%

Phosphoinositide-Dependent Protein Kinases Regulate Cell Cycle Progression Through the SAD Kinase Cdr2 in Fission Yeast

Liu

Sun

et al. 2022

Front. Microbiol.

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Aberration in the control of cell cycle contributes to the development and progression of many diseases including cancers. Ksg1 is a Schizosaccharomyces pombe fission yeast homolog of mammalian phosphoinositide-dependent protein kinase 1 (PDK1) which is regarded as a signaling hub for human tumorigenesis. A previous study reported that Ksg1 plays an important role in cell cycle progression, however, the underlying mechanism remains elusive. Our genomic library screen for novel elements involved in Ksg1 function identified two serine/threonine kinases, namely SAD family kinase Cdr2 and another PDK1 homolog Ppk21, as multicopy suppressors of the thermosensitive phenotype of ksg1-208 mutant. We found that overexpression of Ppk21 or Cdr2 recovered the defective cell cycle transition of ksg1-208 mutant. In addition, ksg1-208 Δppk21 cells showed more marked defects in cell cycle transition than each single mutant. Moreover, overexpression of Ppk21 failed to recover the thermosensitive phenotype of the ksg1-208 mutant when Cdr2 was lacking. Notably, the ksg1-208 mutation resulted in abnormal subcellular localization and decreased abundance of Cdr2, and Ppk21 deletion exacerbated the decreased abundance of Cdr2 in the ksg1-208 mutant. Intriguingly, expression of a mitotic inducer Cdc25 was significantly decreased in ksg1-208, Δppk21, or Δcdr2 cells, and overexpression of Ppk21 or Cdr2 partially recovered the decreased protein level of Cdc25 in the ksg1-208 mutant. Altogether, our findings indicated that Cdr2 is a novel downstream effector of PDK1 homologs Ksg1 and Ppk21, both of which cooperatively participate in regulating cell cycle progression, and Cdc25 is involved in this process in fission yeast.

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“…Although striking differences in size are observed when comparing between different cell types, size distributions within proliferating cell types show only modest variance in cell size, or size ‘uniformity’ (Ginzberg et al, 2015) (coefficients of variation, CVs, typically 0.1-0.3 (Scotchman et al, 2021)). The size homogeneity of proliferating cell populations implies the existence of size checkpoints that occur during proliferation and coordinate cell cycle progression and acquisition of cell mass (Amodeo & Skotheim, 2016; Ginzberg et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Characterization of proteome-size scaling by integrative omics reveals mechanisms of proliferation control in cancer

Jones

Higo

Roumeliotis

et al. 2022

Preprint

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Almost all living cells maintain size uniformity through successive divisions. Proteins that sub- or super-scale with size act as rheostats which regulate cell progression. A comprehensive atlas of these proteins is lacking; particularly in cancer cells where both mitogen and growth signalling are dysregulated.Utilising a multi-omic strategy, that integrates quantitative single cell imaging, phosphoproteomic and transcriptomic datasets, we leverage the inherent size heterogeneity of melanoma cells to investigate how peptides, post-translational modifications, and mRNAs scale with cell size to regulate proliferation. We find melanoma cells have different mean sizes, but all retain uniformity. Across the proteome, we identify proteins and phosphorylation events that ‘sub’ and ‘super’ scale with cell size. In particular, G2/M, biosynthetic, and cytoskeletal regulators sub- and super-scale with size. In small cells growth and proliferation processes are tightly coupled by translation which promotes CCND1 accumulation and anabolic increases in mass. Counter intuitively, anabolic growth pathways and translational process are low in large cells, which throttles the expression of factors such as CCND1 and thereby coupling proliferation from anabolic growth. Strikingly, these cells exhibit increased growth and comparable proliferation rates. Mathematical modelling suggests that decoupling growth and proliferative signalling fosters proliferation under mitogenic inhibition. As factors which promote adhesion and actin reorganization super-scale with size or are enriched in large cells, we suggest that growth/proliferation in these cells may be decoupled by cell spreading and mechanics. This study provides one of the first demonstrations of size-scaling phenomena in cancer and how morphology determines the chemistry of the cell.

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

Cited by 15 publications

References 57 publications

Characterizing non-exponential growth and bimodal cell size distributions in fission yeast: An analytical approach

Characterizing non-exponential growth and bimodal cell size distributions in fission yeast: An analytical approach

Phosphoinositide-Dependent Protein Kinases Regulate Cell Cycle Progression Through the SAD Kinase Cdr2 in Fission Yeast

Characterization of proteome-size scaling by integrative omics reveals mechanisms of proliferation control in cancer

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