Superstability of the yeast cell-cycle dynamics: ensuring causality in the presence of biochemical stochasticity

Gene regulatory dynamics are governed by molecular processes and therefore exhibits an inherent stochasticity. However, for the survival of an organism it is a strict necessity that this intrinsic noise does not prevent robust functioning of the system. It is still an open question how dynamical stability is achieved in biological systems despite the omnipresent fluctuations. In this paper we investigate the cell cycle of the budding yeast Saccharomyces cerevisiae as an example of a well-studied organism. We study a genetic network model of 11 genes that coordinate the cell-cycle dynamics using a modeling framework which generalizes the concept of discrete threshold dynamics. By allowing for fluctuations in the process times, we introduce noise into the model, accounting for the effects of biochemical stochasticity. We study the dynamical attractor of the cell cycle and find a remarkable robustness against fluctuations of this kind. We identify mechanisms that ensure reliability in spite of fluctuations: 'Catcher states' and persistence of activity levels contribute significantly to the stability of the yeast cell cycle despite the inherent stochasticity.     

Neutral space analysis for a Boolean network model of the fission yeast cell cycle network

Background

Interactions between genes and their products give rise to complex circuits known as gene regulatory networks (GRN) that enable cells to process information and respond to external stimuli. Several important processes for life, depend of an accurate and context-specific regulation of gene expression, such as the cell cycle, which can be analyzed through its GRN, where deregulation can lead to cancer in animals or a directed regulation could be applied for biotechnological processes using yeast. An approach to study the robustness of GRN is through the neutral space. In this paper, we explore the neutral space of a Schizosaccharomyces pombe (fission yeast) cell cycle network through an evolution strategy to generate a neutral graph, composed of Boolean regulatory networks that share the same state sequences of the fission yeast cell cycle.

Results

Through simulations it was found that in the generated neutral graph, the functional networks that are not in the wildtype connected component have in general a Hamming distance more than 3 with the wildtype, and more than 10 between the other disconnected functional networks. Significant differences were found between the functional networks in the connected component of the wildtype network and the rest of the network, not only at a topological level, but also at the state space level, where significant differences in the distribution of the basin of attraction for the G₁ fixed point was found for deterministic updating schemes.

Conclusions

In general, functional networks in the wildtype network connected component, can mutate up to no more than 3 times, then they reach a point of no return where the networks leave the connected component of the wildtype. The proposed method to construct a neutral graph is general and can be used to explore the neutral space of other biologically interesting networks, and also formulate new biological hypotheses studying the functional networks in the wildtype network connected component.     

Improved flow cytometric analysis of the budding yeast cell cycle

The budding yeast, Saccharomyces cerevisiae has been a remarkably useful model system for the study of eukaryotic cell cycle regulation. Flow cytometric analysis of DNA content in budding yeast has become a standard tool for the analysis of cell cycle progression. However, popular protocols utilizing the DNA binding dye, propidium iodide, suffer from a number of drawbacks that confound accurate analysis by flow cytometry. Here we show the utility of the DNA binding dye, SYTOX Green, in the cell cycle analysis of yeast. Samples analyzed using SYTOX Green exhibited better coefficients of variation, improved linearity between DNA content and fluorescence, and decreased peak drift associated with changes in dye concentration, growth conditions or cell size.     

Integrative analysis of cell cycle control in budding yeast

The adaptive responses of a living cell to internal and external signals are controlled by networks of proteins whose interactions are so complex that the functional integration of the network cannot be comprehended by intuitive reasoning alone. Mathematical modeling, based on biochemical rate equations, provides a rigorous and reliable tool for unraveling the complexities of molecular regulatory networks. The budding yeast cell cycle is a challenging test case for this approach, because the control system is known in exquisite detail and its function is constrained by the phenotypic properties of >100 genetically engineered strains. We show that a mathematical model built on a consensus picture of this control system is largely successful in explaining the phenotypes of mutants described so far. A few inconsistencies between the model and experiments indicate aspects of the mechanism that require revision. In addition, the model allows one to frame and critique hypotheses about how the division cycle is regulated in wild-type and mutant cells, to predict the phenotypes of new mutant combinations, and to estimate the effective values of biochemical rate constants that are difficult to measure directly in vivo.     

Lack of invaginations of the plasma membrane during budding and cell division of Saccharomyces cerevisiae and Schizosaccharomyces pombe

Abstract The plasma membrane of Saccharomyces cerevisiae and Schizosaccharomyces pombe in stationary phase had abundant invaginations. A round uninvaginated area emerged before budding when S. cerevisiae cells were given fresh medium. Middle-sized buds had some invaginations, whereas the neck between the bud and mother had very few. S. pombe which has neither the neck nor the predetermined position to divide had no uninvaginated ring area even in long cells during elongation in fresh medium. However, an uninvaginated ring area emerged as the earliest noticeable stage of cytokinesis. The uninvaginated state of the plasma membrane appeared to be correlated with budding and cell division.     

Quantitative proteomic analysis of the budding yeast cell cycle using acid-cleavable isotope-coded affinity tag reagents

Quantitative profiling of proteins, the direct effectors of nearly all biological functions, will undoubtedly complement technologies for the measurement of mRNA. Systematic proteomic measurement of the cell cycle is now possible by using stable isotopic labeling with isotope-coded affinity tag reagents and software tools for high-throughput analysis of LC-MS/MS data. We provide here the first such study achieving quantitative, global proteomic measurement of a time-course gene expression experiment in a model eukaryote, the budding yeast Saccharomyces cerevisiae, during the cell cycle. We sampled 48% of all predicted ORFs, and provide the data, including identifications, quantitations, and statistical measures of certainty, to the community in a sortable matrix. We do not detect significant concordance in the dynamics of the system over the time-course tested between our proteomic measurements and microarray measures collected from similarly treated yeast cultures. Our proteomic dataset therefore provides a necessary and complementary measure of eukaryotic gene expression, establishes a rich database for the functional analysis of S. cerevisiae proteins, and will enable further development of technologies for global proteomic analysis of higher eukaryotes.     

Kinetic analysis of a molecular model of the budding yeast cell cycle

The molecular machinery of cell cycle control is known in more detail for budding yeast, Saccharomyces cerevisiae, than for any other eukaryotic organism. In recent years, many elegant experiments on budding yeast have dissected the roles of cyclin molecules (Cln1-3 and Clb1-6) in coordinating the events of DNA synthesis, bud emergence, spindle formation, nuclear division, and cell separation. These experimental clues suggest a mechanism for the principal molecular interactions controlling cyclin synthesis and degradation. Using standard techniques of biochemical kinetics, we convert the mechanism into a set of differential equations, which describe the time courses of three major classes of cyclin-dependent kinase activities. Model in hand, we examine the molecular events controlling "Start" (the commitment step to a new round of chromosome replication, bud formation, and mitosis) and "Finish" (the transition from metaphase to anaphase, when sister chromatids are pulled apart and the bud separates from the mother cell) in wild-type cells and 50 mutants. The model accounts for many details of the physiology, biochemistry, and genetics of cell cycle control in budding yeast.     

Isolation of acdc28 mutation that abrogates the dependence of S phase on completion of M phase of the budding yeast cell cycle

We have isolated a mutation in the budding yeastSaccharomyces cerevisisae CDC28 gene that allowscdc13 cells, carrying damaged DNA, to continue with the cell division cycle. Whilecdc13 mutant cells are arrested as largebudded cells at the nonpermissive temperature 37‡C, thecdc13 cdc28 double mutant culture showed cells with one or more buds, most of which showed apical growth. The additional buds emerged without the intervening steps of nuclear division and cell separation. We suggest that thecdc28 mutation abrogates a checkpoint function and allows cells with damaged or incompletely replicated DNA an entry to another round of cell cycle and bypasses the mitotic phase of the cell cycle.     

蛋白质的磷酸化作用和泛肽化降解作用与芽殖酵母细胞周期的调控

在芽殖酵母（Ｓａｃｃｈａｒｏｍｙｃｅｓｃｅｒｅｖｉｓｉａｅ）细胞中，Ｇ１期的三种ｃｙｃｌｉｎｓ和Ｓ、Ｍ期的五种ｃｙｃｌｉｎｓ之周期性的合成和分解调节着Ｃｄｃ２８的活性，驱动细胞周期的正常运转。除了ＣＤＫ的磷酸化作用外，蛋白质的泛肽化降解作用间接或直接调控细胞周期：ＣＤＣ３４泛肽化途径通过降解Ｃｄｃ２８的专一抑制子而起始ＤＮＡ复制；ＡＰＣ泛肽化途径通过降解Ｍ期后期的抑制子和Ｍ期ｃｙｃｌｉｎｓ，使姐妹染色体分离和Ｍ期终止。     

Modelling the fission yeast cell cycle.

The molecular networks regulating basic physiological processes in a cell can be converted into mathematical equations (eg differential equations) and solved by a computer. The division cycle of eukaryotic cells is an important example of such a control system, and fission yeast is an excellent test organism for the computational modelling approach. The mathematical model is tested by simulating wild-type cells and many known cell cycle mutants. This paper describes an example where this approach is useful in understanding multiple rounds of DNA synthesis (endoreplication) in fission yeast cells that lack the main (B-type) mitotic cyclin, Cdc13. It is proposed that the key physiological variable driving progression through the cell cycle during balanced growth and division is the mass/DNA ratio, rather than the mass/nucleus ratio.     

Time scale and dimension analysis of a budding yeast cell cycle model

Background  

The progress through the eukaryotic cell division cycle is driven by an underlying molecular regulatory network. Cell cycle progression can be considered as a series of irreversible transitions from one steady state to another in the correct order. Although this view has been put forward some time ago, it has not been quantitatively proven yet. Bifurcation analysis of a model for the budding yeast cell cycle has identified only two different steady states (one for G1 and one for mitosis) using cell mass as a bifurcation parameter. By analyzing the same model, using different methods of dynamical systems theory, we provide evidence for transitions among several different steady states during the budding yeast cell cycle.     

Stage-dependent density effect in the cell cycle of budding yeast

Yeasts in culture media grow exponentially in early period but eventually stop growing. The saturation of population growth is due to "density effect". The budding yeast, Saccharomyces cerevisiae, is known to exhibit a stage-dependent cell division. Daughter cell, which gives no birth, has longer generation time than mother, because daughter needs maturity time. So far, investigations have been restricted in exponential or non-crowding state; very little is known for the stage dependence of density effect. Here we present a lattice gas model to explore the population dynamics of crowding period. We compare theoretical results with experimental data, and find a stage-dependent density effect. Although small daughter cells can develop to a critical size, the reproduction of large daughter cells suddenly stops when the total density exceeds some critical level. Our results imply the existence of an inhibitor that specifically halts the reproduction of matured daughter cell.     

不同温度下酿酒酵母细胞分裂周期蛋白Cdc5在有丝分裂中的分子动力学研究

[目的] 探究不同温度下酿酒酵母细胞分裂周期蛋白Cdc5蛋白在有丝分裂中的分子动力学变化。[方法] 本研究以酿酒酵母（Saccharomyces cerevisiae）为材料,采用活细胞成像的方法,探究Cdc5蛋白在不同温度下在酿酒酵母有丝分裂过程中的精细分子动力学变化;通过测量OD₅₉₅绘制生长曲线图,看其宏观的分裂情况是否与微观下Cdc5蛋白的分子动力学变化一致;利用流式细胞术检测细胞的细胞周期变化的情况。[结果] 在胞质分裂时,Cdc5蛋白从母细胞进入子细胞,并在芽颈处发生聚集。25℃条件下细胞中Cdc5蛋白在芽颈处的聚集时间长,37℃条件下Cdc5蛋白在芽颈处聚集时间短,两者间存在显著差异;但两个温度下,细胞中Cdc5蛋白的表达量没有显著性差异。同时,温度也会影响Cdc5蛋白在降解过程中的动力学行为,包括Cdc5蛋白在母细胞与子细胞中荧光强度峰值出现的次数和时间。生长曲线结果显示,酿酒酵母单一细胞分裂周期的变化影响了其宏观的细胞生长,且酵母分裂速度越快,子细胞长宽比越小;细胞周期结果表明,37℃下Cdc5蛋白的动力学变化与酿酒酵母细胞周期变化一致,酿酒酵母细胞周期从G₀/G₁期进入S期,亦加速了酿酒酵母的分裂。[结论] 本研究首次探究了不同温度下酿酒酵母有丝分裂中Cdc5蛋白的精细分子动力学及对应的酵母的宏观生长情况,结果表明温度会对Cdc5蛋白的动力学产生影响,且其精细分子动力学与酿酒酵母的分裂速度成正相关,该结果为进一步研究其在细胞有丝分裂中的功能提供了前期研究基础。     

A cell cycle checkpoint monitors cell morphogenesis in budding yeast

Checkpoint controls are regulatory pathways that inhibit cell cycle progression in cells that have not faithfully completed a prior step in the cell cycle. In the budding yeast Saccharomyces cerevisiae, DNA replication and spindle assembly are monitored by checkpoint controls that prevent nuclear division in cells that have failed to complete these processes. During the normal cell cycle, bud formation is temporally coincident with DNA replication and spindle assembly, and the nucleus divides along the mother-bud axis in mitosis. In this report, we show that inhibition of bud formation also causes a dramatic delay in nuclear division. This allows cells to recover from a transient disruption of cell polarity without becoming binucleate. The delay occurs after DNA replication and spindle assembly, and results from delayed activation of the master cell cycle regulatory kinase, Cdc28. Cdc28 activation is inhibited by phosphorylation of Cdc28 on tyrosine 19, and by delayed accumulation of the B-type cyclins Clb1 and Clb2. These results suggest the existence of a novel checkpoint that monitors cell morphogenesis in budding yeast.     

The fission yeast cell cycle control gene cdc2: isolation of a sequence suc1 that suppresses cdc2 mutant function

Summary A DNA fragment called suc1 has been found to rescue cells mutated in the cell cycle control gene cdc2 of the fission yeast Schizosaccharomyces pombe. The suppressing activity of suc1 is observed when it is present on a multicopy number plasmid. The gene does not hybridise to cdc2 and maps elsewhere in the genome. Its effect is cdc2 allele specific suggesting that it interacts directly with the cdc2 gene function.     

The dynamics of yeast telomeres and silencing proteins through the cell cycle

Genes integrated near the telomeres of budding yeast have a variegated pattern of gene repression that is mediated by the silent information regulatory proteins Sir2p, Sir3p, and Sir4p. Immunolocalization and fluorescence in situ hybridization (FISH) reveal 6-10 perinuclear foci in which silencing proteins and subtelomeric sequences colocalize, suggesting that these are sites of Sir-mediated repression. Telomeres lacking subtelomeric repeat elements and the silent mating locus, HML, also localize to the periphery of the nucleus. Conditions that disrupt telomere proximal repression disrupt the focal staining pattern of Sir proteins, but not necessarily the localization of telomeric DNA. To monitor the telomere-associated pools of heterochromatin-binding proteins (Sir and Rap1 proteins) during mitotic cell division, we have performed immunofluorescence and telomeric FISH on populations of yeast cells synchronously traversing the cell cycle. We observe a partial release of Rap1p from telomeres in late G2/M, although telomeres appear to stay clustered during G2-phase and throughout mitosis. A partial release of Sir3p and Sir4p during mitosis also occurs. This is not observed upon HU arrest, although other types of DNA damage cause a dramatic relocalization of Sir and Rap1 proteins. The observed cell cycle dynamics were confirmed by direct epifluorescence of a GFP-Rap1p fusion. Using live GFP fluorescence we show that the diffuse mitotic distribution of GFP-Rap1p is restored to the interphase pattern of foci in early G1-phase.