Logical analysis of the budding yeast cell cycle

The budding yeast Saccharomyces cerevisiae is a model organism that is commonly used to investigate control of the eukaryotic cell cycle. Moreover, because of the extensive experimental data on wild type and mutant phenotypes, it is also particularly suitable for mathematical modelling and analysis. Here, I present a new Boolean model of the budding yeast cell cycle. This model is consistent with a wide range of wild type and mutant phenotypes and shows remarkable robustness against perturbations, both to reaction times and the states of component genes/proteins. Because of its simple logical nature, the model is suitable for sub-network analysis, which can be used to identify a four node core regulatory circuit underlying cell cycle regulation. Sub-network analysis can also be used to identify key sub-dynamics that are essential for viable cell cycle control, as well as identifying the sub-dynamics that are most variable between different mutants.     

Computer evaluation of network dynamics models with application to cell cycle control in budding yeast

Cellular processes are governed by complex networks of interacting genes and proteins. Theoretical molecular biologists attempt to describe these processes via mathematical models by writing biochemical reaction equations. Modellers are building increasingly larger and complex mathematical models to describe these cellular processes, making model evaluation a time consuming and difficult task. The authors describe an automatable process for model evaluation and a software system that implements this process. The software is adaptable to many types of models and is freely available along with all needed data files. The cell cycle control system for budding yeast is known in fine detail and constrained by more than 100 phenotypic observations in mutant strains. As an example, the authors apply their process to a model of cell cycle control in budding yeast containing dozens of regulatory equations and explaining nearly all of the known mutant phenotypes.     

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。     

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.     

Altered states: programmed proteolysis and the budding yeast cell cycle

The recent identification of an essential RING-H2 finger protein in the SCF E3 ubiquitin ligase complex of budding yeast has uncovered a family of related E3 enzymes, including the other main cell cycle E3 complex, the anaphase promoting complex (APC). Recent insights into APC-dependent proteolysis include a novel protease activity that dissolves cohesion between sister chromatids at anaphase, and a crucial phosphatase, Cdc14, whose release from the nucleolus eliminates cyclin-dependent kinase activity and thereby drives exit from mitosis.     

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.     

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.     

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.     

Effect of tunicamycin on cell cycle progression in budding yeast

Tunicamycin, an inhibitor of one of the earliest steps in the synthesis of N-linked oligosaccharides, prevents bud formation and growth in Saccharomyces cerevisiae cells that are either growing exponentially or recovering from different cell cycle arrests at start. Analysis of tunicamycin-treated cells by flow microfluorometry clearly shows that cells have a postsynthetic DNA content, but there is no evidence of an increase in binucleate cells. Therefore tunicamycin affects bud emergence and initiation of DNA synthesis, two events correlated under physiological conditions, in different ways. A bulk glycoprotein synthesis is shown to be required for bud emergence and localized chitin deposition, probably to sustain directional secretory vesicle transport, which allows polar growth of the bud. No evidence for a glycoprotein requirement for entrance into the S phase is obtained from the present experiments.     

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.     

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.     

Uncovering novel cell cycle players through the inactivation of securin in budding yeast

Budding yeast securin/Pds1p, an inhibitor of the anaphase activator separase/Esp1p, is involved in several checkpoint pathways and in promoting Esp1p's nuclear localization. Using a modified synthetic genetic array (SGA) screen for genes that become essential in the absence of Pds1p, we uncovered roles for uncharacterized genes in cell cycle processes, including Esp1p activation.     

芽残酵母PHO85基因对细胞周期调控的影响

By homo-recombination with yeast intergrating plasmids, a serial of haploid mutants of budding yeast YPH499 had been constructed, which included pho85 delta strain YPH600, pho85 delta cln1 delta strain YPH610, cln1 delta cln2 delta strain YPH640 and galactose inducible strain YPH630 (pho85 delta cln1 delta cln2 delta (GAL1-10PHO85)). By analyzing the growth rate of different strains, we concluded that PHO85 gene have greater influence than CLN1 and CLN2 genes on cell growth control. After transferred from galactose media to glucose media, the tri-mutant cells collected at intervals were observed with microscope and analyzed by FACS. The results showed that the tri-mutant cells arrest in G1 phase when they were transferred to glucose media.     

Identification of responsive gene modules by network-based gene clustering and extending: application to inflammation and angiogenesis

Background  

Cell responses to environmental stimuli are usually organized as relatively separate responsive gene modules at the molecular level. Identification of responsive gene modules rather than individual differentially expressed (DE) genes will provide important information about the underlying molecular mechanisms. Most of current methods formulate module identification as an optimization problem: find the active sub-networks in the genome-wide gene network by maximizing the objective function considering the gene differential expression and/or the gene-gene co-expression information. Here we presented a new formulation of this task: a group of closely-connected and co-expressed DE genes in the gene network are regarded as the signatures of the underlying responsive gene modules; the modules can be identified by finding the signatures and then recovering the "missing parts" by adding the intermediate genes that connect the DE genes in the gene network.