A model for restriction point control of the mammalian cell cycle

Inhibition of protein synthesis by cycloheximide blocks subsequent division of a mammalian cell, but only if the cell is exposed to the drug before the "restriction point" (i.e. within the first several hours after birth). If exposed to cycloheximide after the restriction point, a cell proceeds with DNA synthesis, mitosis and cell division and halts in the next cell cycle. If cycloheximide is later removed from the culture medium, treated cells will return to the division cycle, showing a complex pattern of division times post-treatment, as first measured by Zetterberg and colleagues. We simulate these physiological responses of mammalian cells to transient inhibition of growth, using a set of nonlinear differential equations based on a realistic model of the molecular events underlying progression through the cell cycle. The model relies on our earlier work on the regulation of cyclin-dependent protein kinases during the cell division cycle of yeast. The yeast model is supplemented with equations describing the effects of retinoblastoma protein on cell growth and the synthesis of cyclins A and E, and with a primitive representation of the signaling pathway that controls synthesis of cyclin D.     

细胞周期调控的研究进展

细胞周期是一种非常复杂和精细的调节过程,有大量调节蛋白参与其中。此过程的核心是细胞周期依赖性蛋白激酶（CDKs）。CDKs的激活又依赖于另一类呈细胞周期特异性或时相性表达的细胞周期蛋白（cyclins）,而CDKs调节的关键步骤是细胞周期检查点。PLKs是多种细胞周期检查点的主要调节因子,Aurora蛋白激酶主要在细胞有丝分裂期起作用。本文就上述因素在细胞周期进程中的作用作一综述。     

A rapid method to determine the mammalian cell cycle

A method was developed for determining the duration of the mammalian cell cycle and each of its major phases, mitosis, G1, DNA synthetic period, and G2. Mitotic time was determined by assessment of the mitotic index at intervals after cells collected in mitosis and stored at 4 °C were reincubated at 37 °C. The duration of the three remaining phases was derived from a graphic representation of the uptake of ³H-thymidine by a synchronous population of cells grown directly in scintillation vials. The scintillation counting method for determination of these parameters is advantageous over methods using autoradiography in that the investigator's bias in scoring cells is eliminated. Complex mathematical interpretations are unnecessary, and the data obtained from the scintillation counter are readily processed. Results from scintillation counting and autoradiographic methods are shown to be comparable.     

A checkpoint-oriented cell cycle simulation model

Modeling and in silico simulations are of major conceptual and applicative interest in studying the cell cycle and proliferation in eukaryotic cells. In this paper, we present a cell cycle checkpoint-oriented simulator that uses agent-based simulation modeling to reproduce the dynamics of a cancer cell population in exponential growth. Our in silico simulations were successfully validated by experimental in vitro supporting data obtained with HCT116 colon cancer cells. We demonstrated that this model can simulate cell confluence and the associated elongation of the G1 phase. Using nocodazole to synchronize cancer cells at mitosis, we confirmed the model predictivity and provided evidence of an additional and unexpected effect of nocodazole on the overall cell cycle progression. We anticipate that this cell cycle simulator will be a potential source of new insights and research perspectives.     

Cell cycle regulation of the mammalian CDK activator RINGO/Speedy A

Cell cycle progression is regulated by cyclin-dependent kinases (CDKs), whose activation requires the binding of regulatory subunits named cyclins. RINGO/Speedy A is a mammalian protein that has no amino acid sequence homology with cyclins but can activate CDKs. Here we show that RINGO/Speedy A is a highly unstable protein whose expression and phosphorylation are periodically regulated during the cell cycle. RINGO/Speedy A is degraded by the proteasome and the process involves the ubiquitin ligase SCF^Skp2. Overexpression of a stabilized RINGO/Speedy A form results in the accumulation of high levels of RINGO/Speedy A at late stages of mitosis, which interfere with cytokinesis and chromosome decondensation. Our data show that tight regulation of RINGO/Speedy A is important for the somatic cell cycle.

Structured summary

MINT-7226413:RINGO A (uniprotkb:Q5MJ70) physically interacts (MI:0914) with Ubiquitin (uniprotkb:P62988) by anti bait coimmunoprecipitation (MI:0006)MINT-7226431, MINT-7226448:RINGO A (uniprotkb:Q5MJ70) physically interacts (MI:0914) with Skp2 (uniprotkb:Q13309) by anti tag coimmunoprecipitation (MI:0007)     

A deterministic model of the cell cycle

The variability of the duration of the cell cycle is explained by the phenomenon of sensitive dependence upon initial conditions; as may occur in deterministic non-linear systems. Chaotic dynamics of a system is the result of this sensitive dependence. First a deterministic system is formulated that is equivalent to the Smith-Martin transition probability model of the cell cycle. Next the model is extended to a dynamic process that ranges over the cell generations. A deterministic non-linear relationship between the cycle time of the mother and daughter cell is established. It clarifies the variability of mother-daughter correlation for the different cell types. The model is fitted to two different cell cultures; it shows that the graph of the non-linear relation has the same shape for different cell types.     

A model for regulation of the cell cycle incorporating cyclin A, cyclin B and their complexes

Abstract. t. A mathematical model for the cell cycle is proposed that incorporates the known biochemical reactions involving both cyclin A and cyclin B, the interactions of these cyclins with cdc2 and cdk2, and the controlling effects of cdc25 and weel. The model also postulates the existence of an as yet unknown phosphatase involved in the formation of maturation promoting factor. The model produces solutions that agree qualitatively with a wide variety of experimentally observed cell-cycle behavior. Conditions under which the model could explain the initial rapid divisions of embryonic cells and the transition to the slower somatic cell cycle are also discussed.     

The dynamics of cell cycle regulation

Major events of the cell cycle--DNA synthesis, mitosis and cell division-are regulated by a complex network of protein interactions that control the activities of cyclin-dependent kinases. The network can be modeled by a set of nonlinear differential equations and its behavior predicted by numerical simulation. Computer simulations are necessary for detailed quantitative comparisons between theory and experiment, but they give little insight into the qualitative dynamics of the control system and how molecular interactions determine the fundamental physiological properties of cell replication. To that end, bifurcation diagrams are a useful analytical tool, providing new views of the dynamical organization of the cell cycle, the role of checkpoints in assuring the integrity of the genome, and the abnormal regulation of cell cycle events in mutants. These claims are demonstrated by an analysis of cell cycle regulation in fission yeast.     

Mathematical models of cell cycle regulation

The cell division cycle is a fundamental process of cell biology and a detailed understanding of its function, regulation and other underlying mechanisms is critical to many applications in biotechnology and medicine. Since a comprehensive analysis of the molecular mechanisms involved is too complex to be performed intuitively, mathematical and computational modelling techniques are essential. This paper is a review and analysis of recent approaches attempting to model cell cycle regulation by means of protein-protein interaction networks.     

A mathematical model of periodic processes in membranes (with application to cell cycle regulation)

A mathematical model of the regulation of the cell cycle by the plasma membrane is suggested. The model is based on the hypothesis that structural transitions of the cell membrane play an important role in the regulation of cell division. Conditions of transition from the proliferating state to the resting state and back are investigated. Possible qualitative differences between models of the cell cycle of a normal and a tumour cell are pointed out.     

Temperature compensation in the mammalian cell cycle

Random and synchronous V79 cells were shifted from 37.5 °C to temperatures between 29 ° and 41 °C. Intermitotic time determinations of random cultures showed an increase in generation time and a broadening in the distribution of generation times in cells whose cycle spanned the temperature shift, but only a slight increase in generation time after one generation at temperatures between 34 °–40 °C. At 33.5 °C and below there was a stepwise increase in generation time. When cells grown at non-standard temperatures were allowed to habituate for 48 h at the altered temperature prior to analysis, the increase in median intermitotic time was slightly less in comparison to analyses done after only one generation following the temperature step. The Q₁₀ for cell division of cells growing at temperatures from 34 ° to 40 °C was between 1.15 and 1.26, suggesting that the mammalian cell cycle is temperature compensated over a limited (6–7 °C) temperature span. Mammalian cells in culture appear to have the same capacity for temperature compensation in their cell cycle as do unicellular eukaryotes. The fact that cycle time at lower temperatures increases in a discrete manner is taken as evidence for a quantal clock.