Cell Size Control in Yeast

Turner, Jonathan J.; Ewald, Jennifer C.; Skotheim, Jan M.

doi:10.1016/j.cub.2012.02.041

Cited by 304 publications

(371 citation statements)

References 157 publications

(164 reference statements)

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“…Cells have to reach a certain critical size at which cell-cycle transitions are triggered, such as G1-S or G2-mitosis (Ivanov, 1971;Dobrochaev and Ivanov, 2001;Dolznig et al, 2004;Yang et al, 2006;Turner et al, 2012;Robert et al, 2014). Therefore, along the PD it is expected that cells are equal to or smaller than the critical size of dividing cells (L critD ).…”

Section: Determination Of the Pd/td Boundary By The Msc Approach Coinmentioning

confidence: 99%

Longitudinal zonation pattern inArabidopsisroot tip defined by a multiple structural change algorithm

Pacheco-Escobedo

Ivanov

Ransom-Rodríguez

et al. 2016

Ann Bot

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Background and Aims The Arabidopsis thaliana root is a key experimental system in developmental biology. Despite its importance, we are still lacking an objective and broadly applicable approach for identification of number and position of developmental domains or zones along the longitudinal axis of the root apex or boundaries between them, which is essential for understanding the mechanisms underlying cell proliferation, elongation and differentiation dynamics during root development.Methods We used a statistics approach, the multiple structural change algorithm (MSC), for estimating the number and position of developmental transitions in the growing portion of the root apex. Once the positions of the transitions between domains and zones were determined, linear models were used to estimate the critical size of dividing cells (L critD ) and other parameters.Key Results The MSC approach enabled identification of three discrete regions in the growing parts of the root that correspond to the proliferation domain (PD), the transition domain (TD) and the elongation zone (EZ). Simultaneous application of the MSC approach and G2-to-M transition (CycB1;1DB:GFP) and endoreduplication (pCCS52A1:GUS) molecular markers confirmed the presence and position of the TD. We also found that the MADS-box gene XAANTAL1 (XAL1) is required for the wild-type (wt) PD increase in length during the first 2 weeks of growth. Contrary to wt, in the xal1 loss-of-function mutant the increase and acceleration of root growth were not detected. We also found alterations in L critD in xal1 compared with wt, which was associated with longer cell cycle duration in the mutant.Conclusions The MSC approach is a useful, objective and versatile tool for identification of the PD, TD and EZ and boundaries between them in the root apices and can be used for the phenotyping of different genetic backgrounds, experimental treatments or developmental changes within a genotype. The tool is publicly available at www.ibiologia.com.mx/MSC_analysis.

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Section: Determination Of the Pd/td Boundary By The Msc Approach Coinmentioning

confidence: 99%

Longitudinal zonation pattern inArabidopsisroot tip defined by a multiple structural change algorithm

Pacheco-Escobedo

Ivanov

Ransom-Rodríguez

et al. 2016

Ann Bot

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“…In the budding yeast Saccharomyces cerevisiae, cell division is known to be coordinated with cell growth [1][2][3][4][5][6] (reviewed in [7]). This dependence between growth and division is most noticeable in daughter cells that, owing to the asymmetric manner of budding yeast division, are born smaller than their mothers (figure 1).…”

Section: Introductionmentioning

confidence: 99%

Characterization of dependencies between growth and division in budding yeast

Mayhew

Iversen

Hartemink

2017

J. R. Soc. Interface.

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Cell growth and division are processes vital to the proliferation and development of life. Coordination between these two processes has been recognized for decades in a variety of organisms. In the budding yeast Saccharomyces cerevisiae, this coordination or 'size control' appears as an inverse correlation between cell size and the rate of cell-cycle progression, routinely observed in G 1 prior to cell division commitment. Beyond this point, cells are presumed to complete S/G 2 /M at similar rates and in a size-independent manner. As such, studies of dependence between growth and division have focused on G 1 . Moreover, in unicellular organisms, coordination between growth and division has commonly been analysed within the cycle of a single cell without accounting for correlations in growth and division characteristics between cycles of related cells. In a comprehensive analysis of three published time-lapse microscopy datasets, we analyse both intra-and inter-cycle dependencies between growth and division, revisiting assumptions about the coordination between these two processes. Interestingly, we find evidence (i) that S/G 2 /M durations are systematically longer in daughters than in mothers, (ii) of dependencies between S/G 2 /M and size at budding that echo the classical G 1 dependencies, and (iii) in contrast with recent bacterial studies, of negative dependencies between size at birth and size accumulated during the cell cycle. In addition, we develop a novel hierarchical model to uncover inter-cycle dependencies, and we find evidence for such dependencies in cells growing in sugar-poor environments. Our analysis highlights the need for experimentalists and modellers to account for new sources of cell-to-cell variation in growth and division, and our model provides a formal statistical framework for the continued study of dependencies between biological processes.

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“…Moreover, the hysteresis behavior in cell cycle kinetics in response to changes in pheromone concentration is reproduced theoretically using our model [12]. We deduce that Cln3 is the primary driver of reentry and that the accumulation of Far1 directly reinforces arrest.Finally, we confirm that Far1 accumulates slowly to ensure stability against size-dependent increases in Cln3 activity [21], because the small fluctuation of Cln3 level can be filtered due to the increase of CDK-threshold. Whereas fast phosphorylation cycles of Far1 allow rapid responses including rapid activation and reentry.…”

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confidence: 62%

“…However, if a cell enters S phase later, it will waste resources. Therefore, the decision about the G1/S transition point is critical.Experimental studies have demonstrated that the G1/S transition point is connected to the cell volume [19][20][21]. A recent study demonstrated that the switch-like G1/S transition is driven by the degradation of Sic1 and that the timing of Sic1 destruction is set by Cln1/2-Cdc28 [10].…”

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confidence: 99%

Mathematical modeling reveals the mechanisms of feedforward regulation in cell fate decisions in budding yeast

Zou

2015

Quant. Biol.

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The determination of cell fate is one of the key questions of developmental biology. Recent experiments showed that feedforward regulation is a novel feature of regulatory networks that controls reversible cellular transitions. However, the underlying mechanism of feedforward regulation-mediated cell fate decision is still unclear. Therefore, using experimental data, we develop a full mathematical model of the molecular network responsible for cell fate selection in budding yeast. To validate our theoretical model, we first investigate the dynamical behaviors of key proteins at the Start transition point and the G1/S transition point; a crucial three-node motif consisting of cyclin (Cln1/2), Substrate/Subunit Inhibitor of cyclin-dependent protein kinase (Sic1) and cyclin B (Clb5/6) is considered at these points. The rapid switches of these important components between high and low levels at two transition check points are demonstrated reasonably by our model. Many experimental observations about cell fate decision and cell size control are also theoretically reproduced. Interestingly, the feedforward regulation provides a reliable separation between different cell fates. Next, our model reveals that the threshold for the amount of WHIskey (Whi5) removed from the nucleus is higher at the Reentry point in pheromone-arrested cells compared with that at the Start point in cycling cells. Furthermore, we analyze the hysteresis in the cell cycle kinetics in response to changes in pheromone concentration, showing that Cln3 is the primary driver of reentry and Cln1/2 is the secondary driver of reentry. In particular, we demonstrate that the inhibition of Cln1/2 due to the accumulation of Factor ARrest (Far1) directly reinforces arrest. Finally, theoretical work verifies that the three-node coherent feedforward motif created by cell FUSion (Fus3), Far1 and STErile (Ste12) ensures the rapid arrest and reversibility of a cellular state. The combination of our theoretical model and the previous experimental data contributes to the understanding of the molecular mechanisms of the cell fate decision at the G1 phase in budding yeast and will stimulate further biological experiments in future.Keywords: cell fate decision; feedforward mechanism; mathematical modeling; hysteresis; reversibility INTRODUCTIONCells from across biological kingdoms are continuously engaged in the process of decision making. Through decision making, unicellular and multicellular organisms take information from their surroundings (including neighboring cells) and process these data through complex signal transduction and genetic circuits to further modulate cellular phenotypes. Therefore, the selection of cell fate in response to both internal and external stimuli is essential in a cell's life [1]. Much progress in understanding the circuitry underlying decision making, as well as the advantages of the underlying strategic logic implemented therein, has come from budding yeast, the simplest eukaryote [2].Mathematical modelling is an important method in ©...

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Cell Size Control in Yeast

Cited by 304 publications

References 157 publications

Longitudinal zonation pattern inArabidopsisroot tip defined by a multiple structural change algorithm

Longitudinal zonation pattern inArabidopsisroot tip defined by a multiple structural change algorithm

Characterization of dependencies between growth and division in budding yeast

Mathematical modeling reveals the mechanisms of feedforward regulation in cell fate decisions in budding yeast

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