Inria, Centre de recherche Inria Saclay-Île-de-France, 91120, Palaiseau, France.
PRC, INRAE, CNRS, Université de Tours UMR PRC, Centre INRAE Val de Loire, 37380, Nouzilly, France.
J Math Biol. 2021 Feb 2;82(3):12. doi: 10.1007/s00285-021-01561-x.
In mammals, female germ cells are sheltered within somatic structures called ovarian follicles, which remain in a quiescent state until they get activated, all along reproductive life. We investigate the sequence of somatic cell events occurring just after follicle activation, starting by the awakening of precursor somatic cells, and their transformation into proliferative cells. We introduce a nonlinear stochastic model accounting for the joint dynamics of the two cell types, and allowing us to investigate the potential impact of a feedback from proliferative cells onto precursor cells. To tackle the key issue of whether cell proliferation is concomitant or posterior to cell awakening, we assess both the time needed for all precursor cells to awake, and the corresponding increase in the total cell number with respect to the initial cell number. Using the probabilistic theory of first passage times, we design a numerical scheme based on a rigorous finite state projection and coupling techniques to compute the mean extinction time and the cell number at extinction time. We find that the feedback term clearly lowers the number of proliferative cells at the extinction time. We calibrate the model parameters using an exact likelihood approach. We carry out a comprehensive comparison between the initial model and a series of submodels, which helps to select the critical cell events taking place during activation, and suggests that awakening is prominent over proliferation.
在哺乳动物中，雌性生殖细胞被包裹在称为卵巢滤泡的体细胞结构中，这些滤泡在生殖生命过程中一直处于静止状态，直到被激活。我们研究了滤泡激活后立即发生的体细胞事件的顺序，从前体细胞的唤醒开始，并研究它们如何转化为增殖细胞。我们引入了一个非线性随机模型，该模型考虑了两种细胞类型的联合动力学，使我们能够研究增殖细胞对前体细胞的潜在反馈的影响。为了解决细胞增殖是否与细胞唤醒同时发生或滞后于细胞唤醒的关键问题，我们评估了所有前体细胞唤醒所需的时间，以及相对于初始细胞数量的总细胞数量的相应增加。我们利用首达时的概率理论，设计了一种基于严格的有限状态投影和耦合技术的数值方案，以计算平均灭绝时间和灭绝时间的细胞数量。我们发现，反馈项明显降低了灭绝时间的增殖细胞数量。我们使用精确似然方法校准模型参数。我们对初始模型和一系列子模型进行了全面比较，这有助于选择激活过程中发生的关键细胞事件，并表明唤醒比增殖更为重要。
