Laboratoire de Physique de l'Ecole Normale Supérieure, CNRS, Ecole Normale Supérieure, PSL University, Sorbonne Université, Université Paris-Diderot, Paris, France.
Institut de Biologie de l'ENS (IBENS), Ecole Normale Supérieure, PSL University, CNRS, INSERM, Paris, France.
Phys Rev E. 2020 Jan;101(1-1):012411. doi: 10.1103/PhysRevE.101.012411.
The dynamics of several mesoscopic biological structures depend on the interplay of growth through the incorporation of components of different sizes laterally diffusing along the cell membrane, and loss by component turnover. In particular, a model of such an out-of-equilibrium dynamics has recently been proposed for postsynaptic scaffold domains, which are key structures of neuronal synapses. It is of interest to estimate the lifetime of these mesoscopic structures, especially in the context of synapses where this time is related to memory retention. The lifetime of a structure can be very long as compared to the turnover time of its components and it can be difficult to estimate it by direct numerical simulations. Here, in the context of the model proposed for postsynaptic scaffold domains, we approximate the aggregation-turnover dynamics by a shot-noise process. This enables us to analytically compute the quasistationary distribution describing the sizes of the surviving structures as well as their characteristic lifetime. We show that our analytical estimate agrees with numerical simulations of a full spatial model, in a regime of parameters where a direct assessment is computationally feasible. We then use our approach to estimate the lifetime of mesoscopic structures in parameter regimes where computer simulations would be prohibitively long. For gephyrin, the scaffolding protein specific to inhibitory synapses, we estimate a lifetime longer than several months for a scaffold domain when the single gephyrin protein turnover time is about half an hour, as experimentally measured. While our focus is on postsynaptic domains, our formalism and techniques should be applicable to other biological structures that are also formed by a balance of condensation and turnover.
几个介观生物结构的动力学取决于通过侧向扩散到细胞膜上的不同大小的成分的掺入而进行的生长以及通过成分周转率的损失之间的相互作用。特别是,最近已经提出了一种用于突触后支架域的这种非平衡动力学的模型,突触后支架域是神经元突触的关键结构。估计这些介观结构的寿命是很有意义的,特别是在与记忆保留有关的突触中。与组成部分的周转率相比,结构的寿命可能非常长,并且通过直接数值模拟很难估计它。在这里,在针对突触后支架域提出的模型的背景下,我们通过噪声过程来近似聚集-周转率动力学。这使我们能够分析计算描述存活结构大小及其特征寿命的准稳态分布。我们表明,我们的分析估计与全空间模型的数值模拟在计算上可行的参数范围内相吻合。然后,我们使用我们的方法来估计在计算机模拟可能过长的参数范围内介观结构的寿命。对于特定于抑制性突触的支架蛋白 gephyrin,当单个 gephyrin 蛋白周转率约为半小时,如实验测量所示时,我们估计支架域的寿命超过几个月。虽然我们的重点是突触后域,但我们的形式和技术应该适用于其他通过冷凝和周转率平衡形成的生物结构。