Sturrock Marc, Dawes Adriana T
Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
Department of Mathematics, The Ohio State University, 231 West 18th Avenue, Columbus, OH 43210, USA Department of Molecular Genetics, The Ohio State University, 231 West 18th Avenue, Columbus, OH 43210, USA.
J R Soc Interface. 2015 May 6;12(106). doi: 10.1098/rsif.2015.0150.
Cell polarization is a ubiquitous process which results in cellular constituents being organized into discrete intracellular spatial domains. It occurs in a variety of cell types, including epithelial cells, immune system cells and neurons. A key player in this process is the Par protein family whose asymmetric localization to anterior and posterior parts of the cell is crucial for proper division and cell fate specification. In this paper, we explore a stochastic analogue of the temporal model of Par protein interactions first developed in Dawes & Munro (Dawes and Munro 2011 Biophys. J. 101, 1412-1422. (doi:10.1016/j.bpj.2011.07.030)). We focus on how protein abundance influences the behaviour of both the deterministic and stochastic versions of the model. In Dawes & Munro (2011), it was found that bistable behaviour in the temporal model of Par protein led to the existence of complementary domains in the corresponding spatio-temporal model. Here, we find that the corresponding temporal stochastic model permits switching behaviour (the model solution 'jumps' between steady states) for lower protein abundances, whereas for higher protein abundances the stochastic and deterministic models are in good agreement (the model solution evolves to one of two steady states). This led us to the testable hypothesis that cells with lower abundances of Par protein may be more sensitive to external cues, whereas cells with higher abundances of Par protein may be less sensitive to external cues. In order to gain more control over the precise abundance of Par protein, we proposed and explored a second model (again, examining both deterministic and stochastic versions) in which the total number of Par molecules is conserved. We found that this model required an additional dimerization reaction in the cytoplasm in order for bistable and switching behaviour to be found. Once this additional reaction was included, we found that both the first and second models gave qualitatively similar results but in different regions of the parameter space, suggesting a further regulatory mechanism that cells could potentially use to modulate their response to external signals.
细胞极化是一个普遍存在的过程,它导致细胞成分被组织成离散的细胞内空间域。它发生在多种细胞类型中,包括上皮细胞、免疫系统细胞和神经元。这一过程中的一个关键因素是Par蛋白家族,其在细胞前部和后部的不对称定位对于正确的分裂和细胞命运决定至关重要。在本文中,我们探索了Dawes和Munro(Dawes and Munro 2011 Biophys. J. 101, 1412 - 1422. (doi:10.1016/j.bpj.2011.07.030))首次开发的Par蛋白相互作用时间模型的一个随机类似物。我们关注蛋白质丰度如何影响该模型的确定性和随机版本的行为。在Dawes和Munro(2011年)中,发现Par蛋白时间模型中的双稳态行为导致了相应时空模型中互补域的存在。在这里,我们发现相应的时间随机模型在较低蛋白质丰度时允许切换行为(模型解在稳态之间“跳跃”),而在较高蛋白质丰度时,随机模型和确定性模型吻合良好(模型解演化为两个稳态之一)。这使我们得出一个可检验的假设,即Par蛋白丰度较低的细胞可能对外部信号更敏感,而Par蛋白丰度较高的细胞可能对外部信号不太敏感。为了更好地控制Par蛋白的精确丰度,我们提出并探索了第二个模型(同样,同时研究确定性和随机版本),其中Par分子的总数是守恒的。我们发现,为了找到双稳态和切换行为,该模型需要在细胞质中进行额外的二聚化反应。一旦包含了这个额外反应,我们发现第一个和第二个模型在定性上给出了相似的结果,但在参数空间的不同区域,这表明细胞可能潜在地用于调节其对外部信号反应的另一种调节机制。