Dataset Information

Lang2024 - Cell cycle model explains compartment-resolved dynamics of 16 observables in RPE1 cells

ABSTRACT: This model provides a molecularly detailed description of the biochemical reaction networks governing the mammalian cell cycle, including the restriction point, the G1S, G2/M and metaphase/anaphase transitions. Kinetic laws are described with mass action kinetics. The reaction network includes DNA, (phospho)proteins and complexes, but omits mRNAs for simplicity. To estimate the model parameters, time courses of eight cell cycle regulators in two compartments were reconstructed from single cell snapshot measurements. The resulting optimization problem was defined in PEtab (see https://github.com/paulflang/cell_cycle_petab) and solved with the parallel global optimisation metaheuristic saCeSS.

SUBMITTER: Paul F Lang

PROVIDER: MODEL2401050001 | BioModels | 2024-01-15

REPOSITORIES: BioModels

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	MODEL2401050001?filename=v4.0.0_optimized.xml	Xml

Items per page:

1 - 1 of 1

Publications

Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells.

Lang Paul F PF Penas David R DR Banga Julio R JR Weindl Daniel D Novak Bela B

PLoS computational biology 20240108 1

The mammalian cell cycle is regulated by a well-studied but complex biochemical reaction system. Computational models provide a particularly systematic and systemic description of the mechanisms governing mammalian cell cycle control. By combining both state-of-the-art multiplexed experimental methods and powerful computational tools, this work aims at improving on these models along four dimensions: model structure, validation data, validation methodology and model reusability. We developed a c ...[more]

PMID: 38190398

Similar Datasets

Project description:This 89-node Boolean model of mammalian growth factor signaling can reproduce oscillations in PI3K signaling in cycling cells, and links these oscillations to the regulatory networks that drive each phase of cell cycle progression, as well as apoptosis. It builds on our previous work on modeling cell cycle progression as the interaction of two linked multi-stable switches (Deritei et al, Sci Rep 6:21957, 2016) and extends it to capture the role of Plk1 in cell cycle progression. The resulting model reproduces the following experimentally documented cell behaviors: — cyclic PI3K/AKT1 activity in dividing cells, which remain in sync with the cell cycle — apoptosis in response to prolonged mitosis or mitotic catastrophe — four distinct, experimentally documented cell fates caused by Plk1 inhibition, depending on the timing of Plk1 loss; namely, G2 arrest, mitotic catastrophe, premature anaphase and chromosome mis-segregation leading to aneuploidy, and failure to complete cytokinesis following telophase, which can lead to genome duplication — failure of cytokinesis and accumulation of binucleate telophase cells driven by hyperactive PI3K, hyperactive Ak1, or FoxO inhibition. — the effect of a large number of knockdown / forced activation mutations Testable predictions: — PI3K degradation in response to high PI3K activation is driven by the Neddl4 ubiquitin ligase activated by PLCγ, while its re-synthesis requires nuclear re-accumulation of FoxO3. — The degradation/re-synthesis cycle of PI3K occurs twice per division cycle, synchronized by Plk1-mediated inhibition of FoxO3 during metaphase/anaphase. — Cells in which PI3K is inhibited after the start of DNA synthesis can nevertheless pre-commit to another cell cycle in the presence of saturating growth stimulation (passing the restriction point in late metaphase), albeit at lower rates than wild-type cells. — Cell cycle defects in response to PI3K/Ak1 over-activation or FoxO knockdown are driven by a loss of Plk1 in telophase.