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一种新的芽殖酵母起始转换整合模型的实验测试

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

作者信息

Adames Neil R, Schuck P Logan, Chen Katherine C, Murali T M, Tyson John J, Peccoud Jean

机构信息

Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061

Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061.

出版信息

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

DOI:10.1091/mbc.E15-06-0358
PMID:26310445
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4710230/
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.

摘要

细胞周期由双稳态分子开关组成,这些开关控制着细胞间期(G1和G2)与DNA复制期(S)以及DNA在子细胞间分配期(M)之间的转换。近年来,芽殖酵母G1-S转换(起始点)的许多分子细节已被阐明,特别是关于其由于正反馈机制而呈现的开关样行为。这些结果促使我们重新评估并扩展先前的酵母细胞周期数学模型。新模型纳入了Whi3对Cln3活性的抑制、Whi5对SBF和MBF转录因子的抑制,以及G1-S细胞周期蛋白对Whi5的反馈抑制。我们通过模拟文献中未描述的各种突变体来测试模型的准确性。然后我们构建了这些新型突变菌株,并将观察到的表型与模型模拟结果进行比较。本文报道的实验结果导致了模型的进一步修改,这将在后续文章中详细描述。我们的研究证明了在协同努力中结合模型设计、模拟和测试以更好地理解复杂生物网络的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/4a3938f1dca1/3966fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/d4b6247f2147/3966fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/c737d9de7e52/3966fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/94b7854635b0/3966fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/fac332a77f38/3966fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/6a37587060e7/3966fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/aabd65c9d65d/3966fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/7466b8eccabd/3966fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/12d440838215/3966fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/4a3938f1dca1/3966fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/d4b6247f2147/3966fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/c737d9de7e52/3966fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/94b7854635b0/3966fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/fac332a77f38/3966fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/6a37587060e7/3966fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/aabd65c9d65d/3966fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/7466b8eccabd/3966fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/12d440838215/3966fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/963d/4710230/4a3938f1dca1/3966fig9.jpg

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Adaptive imaging cytometry to estimate parameters of gene networks models in systems and synthetic biology.用于估计系统生物学和合成生物学中基因网络模型参数的自适应成像细胞术。
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