Abstract:Although current textbook explanations of cell-cycle control in eukaryotes emphasize the periodic activation of cyclin-dependent protein kinases (CDKs), recent experimental observations suggest a significant role for the periodic activation and inactivation of a CDK-counteracting protein phosphatase 2A with a B55δ subunit (PP2A:B55δ), during mitotic cycles in frog-egg extracts and early embryos. In this paper, we extend an earlier mathematical model of embryonic cell cycles to include experimentally motivated … Show more
“…These known and predicted roles of B55 create a multitude of new positive and negative feedback loops in the network (Fig. 4a ) with interesting dynamical consequences [ 38 ]. Fig.…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
confidence: 99%
“…a Molecular mechanism. Adapted from figure S1 of [ 38 ]. As in earlier figures, solid arrows represent chemical reactions; dashed arrows represent catalytic activities.…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
confidence: 99%
“…b Signal-response curve for PP2A:B55δ. Adapted from figure 5B of [ 38 ]. For a fixed activity of MPF we plot the corresponding steady state activity of PP2A:B55δ, the phosphatase that counteracts certain MPF-driven phosphorylations.…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
confidence: 99%
“…c Signal-response curve for APC. Figure S4 of [ 38 ]; used by permission. For a fixed activity of MPF we plot the corresponding steady state activity of APC, the ubiquitin-conjugating enzyme that labels cyclin B for degradation.…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
confidence: 99%
“…Of special significance is the double-negative feedback loop between Gwl and B55, which (we propose) creates a bistable switch controlled by MPF [ 38 ]. (Let’s call it the BEG switch, for B55-Ensa-Gwl [ 39 ].)…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
In this essay we illustrate some general principles of mathematical modeling in biology by our experiences in studying the molecular regulatory network underlying eukaryotic cell division. We discuss how and why the models moved from simple, parsimonious cartoons to more complex, detailed mechanisms with many kinetic parameters. We describe how the mature models made surprising and informative predictions about the control system that were later confirmed experimentally. Along the way, we comment on the ‘parameter estimation problem’ and conclude with an appeal for a greater role for mathematical models in molecular cell biology.
“…These known and predicted roles of B55 create a multitude of new positive and negative feedback loops in the network (Fig. 4a ) with interesting dynamical consequences [ 38 ]. Fig.…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
confidence: 99%
“…a Molecular mechanism. Adapted from figure S1 of [ 38 ]. As in earlier figures, solid arrows represent chemical reactions; dashed arrows represent catalytic activities.…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
confidence: 99%
“…b Signal-response curve for PP2A:B55δ. Adapted from figure 5B of [ 38 ]. For a fixed activity of MPF we plot the corresponding steady state activity of PP2A:B55δ, the phosphatase that counteracts certain MPF-driven phosphorylations.…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
confidence: 99%
“…c Signal-response curve for APC. Figure S4 of [ 38 ]; used by permission. For a fixed activity of MPF we plot the corresponding steady state activity of APC, the ubiquitin-conjugating enzyme that labels cyclin B for degradation.…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
confidence: 99%
“…Of special significance is the double-negative feedback loop between Gwl and B55, which (we propose) creates a bistable switch controlled by MPF [ 38 ]. (Let’s call it the BEG switch, for B55-Ensa-Gwl [ 39 ].)…”
Section: The Interesting Question Now Is How Various Molecular Componmentioning
In this essay we illustrate some general principles of mathematical modeling in biology by our experiences in studying the molecular regulatory network underlying eukaryotic cell division. We discuss how and why the models moved from simple, parsimonious cartoons to more complex, detailed mechanisms with many kinetic parameters. We describe how the mature models made surprising and informative predictions about the control system that were later confirmed experimentally. Along the way, we comment on the ‘parameter estimation problem’ and conclude with an appeal for a greater role for mathematical models in molecular cell biology.
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.
Cells control the properties of the cytoplasm to ensure proper functioning of biochemical processes. Recent studies showed that cytoplasmic density varies in both physiological and pathological states of cells undergoing growth, division, differentiation, apoptosis, senescence, and metabolic starvation. Little is known about how cellular processes cope with these cytoplasmic variations. Here, we study how a cell cycle oscillator comprising cyclin-dependent kinase (Cdk1) responds to changes in cytoplasmic density by systematically diluting or concentrating cycling Xenopus egg extracts in cell-like microfluidic droplets. We found that the cell cycle maintains robust oscillations over a wide range of deviations from the endogenous density: as low as 0.2× to more than 1.22× relative cytoplasmic density (RCD). A further dilution or concentration from these values arrested the system in a low or high steady state of Cdk1 activity, respectively. Interestingly, diluting an arrested cytoplasm of 1.22× RCD recovers oscillations at lower than 1× RCD. Thus, the cell cycle switches reversibly between oscillatory and stable steady states at distinct thresholds depending on the direction of tuning, forming a hysteresis loop. We propose a mathematical model which recapitulates these observations and predicts that the Cdk1/Wee1/Cdc25 positive feedback loops do not contribute to the observed robustness, supported by experiments. Our system can be applied to study how cytoplasmic density affects other cellular processes.
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