Rationalizing Rac1 and RhoA GTPase signaling: A mathematical approach.
Rationalizing Rac1 and RhoA GTPase signaling: A mathematical approach.
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DOI：
10.1080/21541248.2016.1218406
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发表时间：
2018-05-04
期刊：
影响因子：
--
通讯作者：
Caswell, Patrick T
中科院分区：
文献类型：
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作者：
Hetmanski, Joseph H R;Schwartz, Jean-Marc;Caswell, Patrick T
Rho GTPases的精确时空动态对于有效的细胞迁移至关重要。因此，操纵Rac1和RhoA信号是一种潜在的干预策略，可以消除有害细胞的侵袭和随后的转移；然而，由于串扰和众多的上游调节因子和下游效应因子，GTPase信号传导可能非常复杂。因此，在正式的数学设置中研究Rho GTPase网络可能非常有用。我们最近建立了一个基于布尔逻辑的预测模型，该模型确定了一个对RhoA和Rac1活性至关重要的负反馈回路。在这里，我们讨论了用于研究Rho GTPase动力学的不同数学方法的价值和潜在缺陷，并强调了在给定可用数据和期望输出的情况下选择正确方法的重要性。总的来说，数学方法，特别是当与体外实验迭代结合时，可以在获得新的生物学见解以进一步利用Rho GTPases的活性方面发挥重要作用。
Precise spatiotemporal dynamics of Rho GTPases are essential for efficient cell migration. Manipulating Rac1 and RhoA signaling is thus a potential intervention strategy to abrogate harmful cell invasion and subsequent metastasis; however GTPase signaling can be extremely complicated due to crosstalk and the multitude of upstream regulators and downstream effectors. Studying Rho GTPase networks in a formal mathematical setting can therefore be of great use. We recently built a predictive model based on Boolean logic which identified a negative feedback loop critical for RhoA and Rac1 activity. Here, we discuss the value and potential pitfalls of different mathematical approaches which have been used to study Rho GTPase dynamics, and highlight the importance of choosing the correct approach given the data available and outputs desired. Overall, a mathematical approach, particularly when combined iteratively with in vitro experiments, can be of great use in deriving new biological insight to further harness the activity of Rho GTPases.