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Mol Biol Cell. 2015 Nov 5;26(22):3966-84. doi: 10.1091/mbc.E15-06-0358. Epub 2015 Aug 26.

Experimental testing of a new integrated model of the budding yeast Start transition.

Author information

1
Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061 nadames@vbi.vt.edu.
2
Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061.
3
Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061.
4
Department of Computer Science, Virginia Tech, Blacksburg, VA 24061 ICTAS Center for Systems Biology of Engineered Tissues, Virginia Tech, Blacksburg, VA 24061.
5
Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061 Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061.
6
Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061 ICTAS Center for Systems Biology of Engineered Tissues, Virginia Tech, Blacksburg, VA 24061.

Abstract

The cell cycle is composed of bistable molecular switches that govern the transitions between gap phases (G1 and G2) and the phases in which DNA is replicated (S) and partitioned between daughter cells (M). Many molecular details of the budding yeast G1-S transition (Start) have been elucidated in recent years, especially with regard to its switch-like behavior due to positive feedback mechanisms. These results led us to reevaluate and expand a previous mathematical model of the yeast cell cycle. The new model incorporates Whi3 inhibition of Cln3 activity, Whi5 inhibition of SBF and MBF transcription factors, and feedback inhibition of Whi5 by G1-S cyclins. We tested the accuracy of the model by simulating various mutants not described in the literature. We then constructed these novel mutant strains and compared their observed phenotypes to the model's simulations. The experimental results reported here led to further changes of the model, which will be fully described in a later article. Our study demonstrates the advantages of combining model design, simulation, and testing in a coordinated effort to better understand a complex biological network.

PMID:
26310445
PMCID:
PMC4710230
DOI:
10.1091/mbc.E15-06-0358
[Indexed for MEDLINE]
Free PMC Article

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