Kinetics Behavior of G1-to-S Cell Cycle Phase Transition Model

Spectrins are ubiquitous scaffolding components of the membrane skeleton that organize and stabilize microdomains on both the plasma membrane and the intracellular organelles. By way of their numerous interactions with diverse protein families, they are implicated in various cellular functions. Using small interfering RNA strategy in the WM-266 cell line derived from human melanoma, we found that alphaII-spectrin deficiency is associated with a defect in cell proliferation, which is related to a cell cycle arrest at the G1 phase (first gap phase), as evaluated by DNA analysis and Rb phosphorylation. These observations coincided with elevated expression of the cyclin-dependent kinase inhibitor, p21Cip. Concomitantly, spectrin loss impaired cell adhesion and spreading. These cell adhesion defects were associated with modifications of the actin cytoskeleton, such as loss of stress fibers, alterations of focal adhesions, and modified expression of some integrins. Our results provide novel insights into spectrin functions by demonstrating the involvement of alphaII-spectrin in cell cycle regulation and actin organization.

Preface. Relationship between RAS pathways and cell cycle control M.E. Ewen. Cell-Anchorage, cell cytoskeleton, and Rho-GTPase family in regulation of cell cycle progression I. Tatsuno, et al. The Continuum model and G1-control of the mammalian cell cycle S. Cooper. Histone acetylation and the control of the cell cycle L. Magnaghi-Jaulin, et al. 14-3-3. proteins and growth control V. Baldin. A Cdc7p-Dbf4 protein kinase activity is conserved from yeast to humans L.H. Johnston, et al. Alternative product of the p16/CKDN2A locus connects the Rb and p53 tumor suppressors M.C. James, G. Peters. Phosphorylation-dependent prolyl isomerization: a novel cell cycle regulatory mechanism K.P. Lu. Functions of Pho85 cyclin-dependent kinases in budding yeast J. Moffat, et al. Cell cycle regulation by the Cdc 25 phosphatase family I. Nilsson, I. Hoffmann. Molecular mechanisms of the initiation of oocyte maturation: general and species-specific aspects M. Yamashita, et al. The activation of MAP kinase and p34 cdc2/cyclin B during the meiotic maturation of Xenopus oocytes A. Palmer, A.R. Nebreda. Premature chromatin condensation caused by loss of RCC1 H. Nishijima, et al. HTLV-I tax and cell cycle progression C. Neuveut, K.-T. Jeang. The cell cycle in protozoan parasites C. Doerig, et al. Circadian control of cell division in unicellular organisms M. Tetsuya, C.H. Johnson. Circadian variation of cell proliferation and cell cycle protein expression in man: clinical implicatikons G. Bjarnason, R. Jordan. Molecular switches that govern the balance between proliferation and apoptosis B. Schutte, F.C.S. Ramaekers. Molecular events that regulate cell proliferation: an approach for the development of new anticancer drugs E. Damiens. Abortive oncogeny and cell cycle-mediated events in Alzheimer disease A.K. Raina, et al. Contributors. Index.

Systems Biology Analysis of Human Primary T Cells Identifies SAP145 as Rate Limiting for the G1→S Phase Transition.

To study the mechanism of cells subjected to external electromagnetic fields, the expression of cyclin kinase inhibitor p27 is analyzed in the four cell cycle phases. The regulatory functions are investigated in gap phase1 to synthesis, gap phase 2 to mitotic phase and post mitotic phase transition in the mammalian cell cycle processes. A mathematical model is developed to meet the general cell cycle regulatory network based on the molecular dynamics method. Phase plane analysis results show that the p27 over-expression can lead to the hysteresis effect of cell cycle processes and phase transition delay. It is an universal approach to predict the key regulatory gene in signal transduction pathway.

Cell cycle models that allow multiple random transitions and asymmetric cell division may exhibit a property that has been used to support the transition probability model of the cell cycle: that the absolute value of the difference between sibling cell inter-mitotic times varies from one sibling pair to another and is described by an exponential statistical distribution. Three models that show this property are described, each of which postulates the existence of objects that are partitioned between daughter cells during cell division and whose number influences the duration of the subsequent cell cycle, e.g., surface receptors for growth factors or transcriptional complexes that are carried by sister chromatids. In the first model, sibling cells receive identical numbers of the objects, which are used to perform multiple random transitions that constitute part of the cell cycle. The second model is like the first, except that the partitioning of objects between the newly-formed sibling cells is random. The third model is also like the first, except that all of the objects are passed to one of the sibling cells. These results show that the general mechanisms that are responsible for the dispersion of inter-mitotic times, the correlation between sibling generation times and the apparently exponentially distributed difference between sibling generation times, could be a combination of unequal cell division, multiple random cell cycle transitions and heterogeneity of mitotic cells.

The cellular protein-protein interaction network that governs cellular proliferation (cell cycle) is highly complex. Here, we have developed a novel computational model of human mitotic cell cycle, integrating diverse cellular mechanisms, for the purpose of generating new hypotheses and predicting new experiments designed to help understand complex diseases. The pathogenic state investigated is infection by a human herpesvirus. The model starts at mitotic entry initiated by the activities of Cyclin-dependent kinase 1 (CDK1) and Polo-like kinase 1 (PLK1), transitions through Anaphase-promoting complex (APC/C) bound to Cell division cycle protein 20 (CDC20), and ends upon mitotic exit mediated by APC/C bound to CDC20 homolog 1 (CDH1). It includes syntheses and multiple mechanisms of degradations of the mitotic proteins. Prior to this work, no such comprehensive model of the human mitotic cell cycle existed. The new model is based on a hybrid framework combining Michaelis-Menten and mass action kinetics for the mitotic interacting reactions. It simulates temporal changes in 12 different mitotic proteins and associated protein complexes in multiple states using 15 interacting reactions and 26 ordinary differential equations. We have defined model parameter values using both quantitative and qualitative data and using parameter values from relevant published models, and we have tested the model to reproduce the cardinal features of human mitosis determined experimentally by numerous laboratories. Like cancer, viruses create dysfunction to support infection. By simulating infection of the human herpesvirus, cytomegalovirus, we hypothesize that virus-mediated disruption of APC/C is necessary to establish a unique mitotic collapse with sustained CDK1 activity, consistent with known mechanisms of virus egress. With the rapid discovery of cellular protein-protein interaction networks and regulatory mechanisms, we anticipate that this model will be highly valuable in helping us to understand the network dynamics and identify potential points of therapeutic interventions.

The cellular protein-protein interaction network that governs cellular proliferation (cell cycle) is highly complex. Here, we have developed a novel computational model of human mitotic cell cycle, integrating diverse cellular mechanisms, for the purpose of generating new hypotheses and predicting new experiments designed to help understand complex diseases. The pathogenic state investigated is infection by a human herpesvirus. The model starts at mitotic entry initiated by the activities of Cyclin-dependent kinase 1 (CDK1) and Polo-like kinase 1 (PLK1), transitions through Anaphase-promoting complex (APC/C) bound to Cell division cycle protein 20 (CDC20), and ends upon mitotic exit mediated by APC/C bound to CDC20 homolog 1 (CDH1). It includes syntheses and multiple mechanisms of degradations of the mitotic proteins. Prior to this work, no such comprehensive model of the human mitotic cell cycle existed. The new model is based on a hybrid framework combining Michaelis-Menten and mass action kinetics for the mitotic interacting reactions. It simulates temporal changes in 12 different mitotic proteins and associated protein complexes in multiple states using 15 interacting reactions and 26 ordinary differential equations. We have defined model parameter values using both quantitative and qualitative data and using parameter values from relevant published models, and we have tested the model to reproduce the cardinal features of human mitosis determined experimentally by numerous laboratories. Like cancer, viruses create dysfunction to support infection. By simulating infection of the human herpesvirus, cytomegalovirus, we hypothesize that virus-mediated disruption of APC/C is necessary to establish a unique mitotic collapse with sustained CDK1 activity, consistent with known mechanisms of virus egress. With the rapid discovery of cellular protein-protein interaction networks and regulatory mechanisms, we anticipate that this model will be highly valuable in helping us to understand the network dynamics and identify potential points of therapeutic interventions.

The eukaryotic cell cycle is robustly designed, with interacting molecules organized within a definite topology that ensures temporal precision of its phase transitions. Its underlying dynamics are regulated by molecular switches, for which remarkable insights have been provided by genetic and molecular biology efforts. In a number of cases, this information has been made predictive, through computational models. These models have allowed for the identification of novel molecular mechanisms, later validated experimentally. Logical modeling represents one of the youngest approaches to address cell cycle regulation. We summarize the advances that this type of modeling has achieved to reproduce and predict cell cycle dynamics. Furthermore, we present the challenge that this type of modeling is now ready to tackle: its integration with intracellular networks, and its formalisms, to understand crosstalks underlying systems level properties, ultimate aim of multi-scale models. Specifically, we discuss and illustrate how such an integration may be realized, by integrating a minimal logical model of the cell cycle with a metabolic network.

Introduction: Current Themes on Cell Cycle and Cancer

Addressing data uncertainty of Caulobacter crescentus cell cycles using hybrid Petri nets with fuzzy kinetics.

Different cancer cell lines can have varying responses to the same perturbations or stressful conditions. Cancer cells that have DNA damage checkpoint-related mutations are often more sensitive to gene perturbations including altered Plk1 and p53 activities than cancer cells without these mutations. The perturbations often induce a cell cycle arrest in the former cancer, whereas they only delay the cell cycle progression in the latter cancer. To study crosstalk between Plk1, p53, and G2/M DNA damage checkpoint leading to differential cell cycle regulations, we developed a computational model by extending our recently developed model of mitotic cell cycle and including these key interactions. We have used the model to analyze the cancer cell cycle progression under various gene perturbations including Plk1-depletion conditions. We also analyzed mutations and perturbations in approximately 1800 different cell lines available in the Cancer Dependency Map and grouped lines by genes that are represented in our model. Our model successfully explained phenotypes of various cancer cell lines under different gene perturbations. Several sensitivity analysis approaches were used to identify the range of key parameter values that lead to the cell cycle arrest in cancer cells. Our resulting model can be used to predict the effect of potential treatments targeting key mitotic and DNA damage checkpoint regulators on cell cycle progression of different types of cancer cells.

Mammalian cyclin D-Cdk4 complexes have been characterized as growth factor-responsive cell cycle regulators. Their levels rise upon growth factor stimulation, and they can phosphorylate and thus neutralize Retinoblastoma (Rb) family proteins to promote an E2F-dependent transcriptional program and S-phase entry. Here we characterize the in vivo function of Drosophila Cyclin D (CycD). We find that Drosophila CycD-Cdk4 does not act as a direct G(1)/S-phase regulator, but instead promotes cellular growth (accumulation of mass). The cellular response to CycD-Cdk4-driven growth varied according to cell type. In undifferentiated proliferating wing imaginal cells, CycD-Cdk4 caused accelerated cell division (hyperplasia) without affecting cell cycle phasing or cell size. In endoreplicating salivary gland cells, CycD-Cdk4 caused excessive DNA replication and cell enlargement (hypertrophy). In differentiating eyes, CycD-Cdk4 caused cell enlargement (hypertrophy) in post-mitotic cells. Interaction tests with a Drosophila Rb homolog, RBF, indicate that CycD-Cdk4 can counteract the cell cycle suppressive effects of RBF, but that its growth promoting activity is mediated at least in part via other targets.

Cell cycle regulation in a dinoflagellate, Amphidinium operculatum: identification of the diel entraining cue and a possible role for cyclic AMP

Understanding the details of the cell cycle at the level of individual cells is critical for both cellular biology and cancer research. While existing methods using specific fluorescent markers have advanced our ability to study the cell cycle in cells that adhere to surfaces, there is a clear gap when it comes to non-adherent cells. In this study, we combine a specialized surface to improve cell attachment, the genetically-encoded FUCCI(CA)2 sensor, an automated image processing and analysis pipeline, and a custom machine-learning algorithm. This combined approach allowed us to precisely measure the duration of different cell cycle phases in non-adherent cells.Our method provided detailed information from hundreds of cells under different experimental conditions in a fully automated manner. We validated this approach in two different Acute Myeloid Leukemia (AML) cell lines, NB4 and Kasumi-1, which have unique cell cycle characteristics. Additionally, we tested the impact of drugs affecting the cell cycle in NB4 cells. Importantly, our cell cycle analysis system is freely available and has also been validated for use with adherent cells.In summary, this report introduces a comprehensive, automated method for studying the cell cycle in both adherent and non-adherent cells, offering a valuable tool for cancer research and drug development.

Hdac1-deficiency affects the cell cycle axis Cdc25-Cdk1 causing impaired G2/M phase progression and reduced cardiomyocyte proliferation in zebrafish