Modeling the START transition in the budding yeast cell cycle.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS PLoS Computational Biology Pub Date : 2024-08-02 eCollection Date: 2024-08-01 DOI:10.1371/journal.pcbi.1012048
Janani Ravi, Kewalin Samart, Jason Zwolak
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Abstract

Budding yeast, Saccharomyces cerevisiae, is widely used as a model organism to study the genetics underlying eukaryotic cellular processes and growth critical to cancer development, such as cell division and cell cycle progression. The budding yeast cell cycle is also one of the best-studied dynamical systems owing to its thoroughly resolved genetics. However, the dynamics underlying the crucial cell cycle decision point called the START transition, at which the cell commits to a new round of DNA replication and cell division, are under-studied. The START machinery involves a central cyclin-dependent kinase; cyclins responsible for starting the transition, bud formation, and initiating DNA synthesis; and their transcriptional regulators. However, evidence has shown that the mechanism is more complicated than a simple irreversible transition switch. Activating a key transcription regulator SBF requires the phosphorylation of its inhibitor, Whi5, or an SBF/MBF monomeric component, Swi6, but not necessarily both. Also, the timing and mechanism of the inhibitor Whi5's nuclear export, while important, are not critical for the timing and execution of START. Therefore, there is a need for a consolidated model for the budding yeast START transition, reconciling regulatory and spatial dynamics. We built a detailed mathematical model (START-BYCC) for the START transition in the budding yeast cell cycle based on established molecular interactions and experimental phenotypes. START-BYCC recapitulates the underlying dynamics and correctly emulates key phenotypic traits of ~150 known START mutants, including regulation of size control, localization of inhibitor/transcription factor complexes, and the nutritional effects on size control. Such a detailed mechanistic understanding of the underlying dynamics gets us closer towards deconvoluting the aberrant cellular development in cancer.

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模拟芽殖酵母细胞周期中的 START 过渡。
芽殖酵母(Saccharomyces cerevisiae)被广泛用作研究对癌症发展至关重要的真核细胞过程和生长(如细胞分裂和细胞周期进展)的基础遗传学的模式生物。芽殖酵母细胞周期也是研究得最好的动力学系统之一,因为它的遗传学得到了彻底解决。然而,对细胞开始新一轮 DNA 复制和细胞分裂的关键细胞周期决定点 START 过渡的动力学研究却不足。START 机制包括一个中央细胞周期蛋白依赖性激酶;负责启动过渡、芽形成和启动 DNA 合成的细胞周期蛋白;以及它们的转录调节因子。然而,有证据表明,这一机制比简单的不可逆转换开关更为复杂。激活关键转录调节因子 SBF 需要其抑制因子 Whi5 或 SBF/MBF 单体成分 Swi6 的磷酸化,但不一定两者都需要。此外,抑制剂 Whi5 核输出的时间和机制虽然重要,但对 START 的时间和执行并不关键。因此,有必要为芽殖酵母 START 过渡建立一个综合模型,协调调控和空间动态。我们根据已建立的分子相互作用和实验表型,为芽殖酵母细胞周期中的 START 过渡建立了一个详细的数学模型(START-BYCC)。START-BYCC 重现了基本动态,并正确模拟了约 150 个已知 START 突变体的关键表型特征,包括大小控制的调节、抑制剂/转录因子复合物的定位以及营养对大小控制的影响。对基本动态的如此详细的机理了解使我们更接近于解构癌症中的异常细胞发育。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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