Rule-based modeling and simulations of the inner kinetochore structure

OMICS: A Journal of Integrative Biology

2015

Self Cite

Correct DNA segregation is a fundamental process that ensures the precise and reliable inheritance of genomic information for the propagation of cell life. Eukaryotic cells have evolved a conserved surveillance control mechanism for DNA segregation named the Spindle Assembly Checkpoint (SAC).The SAC ensures that the sister chromatids of the duplicated genome are not separated and distributed to the spindle poles before all chromosomes have been properly linked to the microtubules of the mitotic spindle. Biochemically, the SAC delays cell cycle progression by preventing activation of the anaphase-promoting complex (APC/C) or cyclosome whose activation by Cdc20 is required for sister-chromatid separation; this marks the transition into anaphase. In response to activation of the checkpoint, various species control the activity of both APC/C and Cdc20. However, the underlying regulatory pathways remain largely elusive. In this study, five possible model variants of APC/C regulation were constructed, namely BubR1, Mad2, MCC, MCF2, and an all-pathways model variant. These models were validated with experimental data from the literature. A wide range of parameter values has been tested to find the critical values of the APC/C binding rate. The results show that all variants are able to capture the wild-type behavior of the APC/C. However, only one model variant, which included both MCC as well as BubR1 as potent inhibitors of the APC/C, was able to reproduce both wild-type and mutant type behavior of APC/C regulation. In conclusion, the presented work informs the regulation of fundamental processes such as SAC and APC/C in cell biology and has successfully distinguished between five competing dynamical models using a systems biology approach. The results attest that systems-level approaches are vital for molecular and cell biology.

Section: Resultsmentioning

confidence: 99%

Systems Biology Modeling of Five Pathways for Regulation and Potent Inhibition of the Anaphase-Promoting Complex (APC/C): Pivotal Roles for MCC and BubR1

OMICS: A Journal of Integrative Biology

2015

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“…Quantitative analysis and computational modeling are very important tools to elucidate how such elaborate systems work. So far, mathematical models have helped to enlighten kinetochores structure and with that the mitotic checkpoint mechanism [26,27,28,29,30,32,33,57,58,59,60,61,62,30,32,33,57]. These models helped to pinpoint advantages and problems of putative regulatory mechanisms.…”

Section: Discussionmentioning

confidence: 99%

Active Transport Can Greatly Enhance Cdc20:Mad2 Formation

Henze

2014

IJMS

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To guarantee genomic integrity and viability, the cell must ensure proper distribution of the replicated chromosomes among the two daughter cells in mitosis. The mitotic spindle assembly checkpoint (SAC) is a central regulatory mechanism to achieve this goal. A dysfunction of this checkpoint may lead to aneuploidy and likely contributes to the development of cancer. Kinetochores of unattached or misaligned chromosomes are thought to generate a diffusible “wait-anaphase” signal, which is the basis for downstream events to inhibit the anaphase promoting complex/cyclosome (APC/C). The rate of Cdc20:C-Mad2 complex formation at the kinetochore is a key regulatory factor in the context of APC/C inhibition. Computer simulations of a quantitative SAC model show that the formation of Cdc20:C-Mad2 is too slow for checkpoint maintenance when cytosolic O-Mad2 has to encounter kinetochores by diffusion alone. Here, we show that an active transport of O-Mad2 towards the spindle mid-zone increases the efficiency of Mad2-activation. Our in-silico data indicate that this mechanism can greatly enhance the formation of Cdc20:Mad2 and furthermore gives an explanation on how the “wait-anaphase” signal can dissolve abruptly within a short time. Our results help to understand parts of the SAC mechanism that remain unclear.

“…We thus consider the RMSD of the pairwise distance between elementary molecules [56]:

{paired RMSD}_{p q} = \sqrt{\frac{2}{n^{2} + n} \sum_{i = 1}^{n} \sum_{j = 1}^{i} {(‖ p_{i} - p_{j} ‖ - ‖ q_{i} - q_{j} ‖)}^{2}}

…”

Section: Methodsmentioning

confidence: 99%

“…Recently, a first 3D rule-based model of the inner kinetochore has been proposed based on intracellular proximity between inner kinetochore proteins [56], which suites to cope with combinatorial complexity However, they modeled the S-phase inner kinetochore and used the same geometry for all proteins.…”

Section: Biological Application: Rule-based Spatial Model Of the Humamentioning

confidence: 99%

Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore

Henze

Gruenert

et al. 2013

Cells

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A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models.