Speaker
Description
Female mammals are born with a non-renewable pool of oocytes that underlies the ovarian reserve. The size of the oocyte pool results in great part from a selection process occurring during ovarian development within germ cysts, where clusters of germ cells are surrounded by layers of somatic cells. During selection, oocytes increase in size at the expense of non-selected cells, which are committed to death. We present a multiscale model of oocyte selection, coupling spatial cell organisation with stochastic gene-regulatory dynamics. Implemented in Simuscale, a modular multiscale framework, our 3D agent-based model represents anatomically-realistic germ cysts. Cell fate is driven by a minimal gene-regulatory network accounting for germ-germ and germ-somatic cell interactions. We investigate how cyst geometry and spatial organisation influence oocyte selection. Model parameters are calibrated to meet quantitative specifications on the selection rate. We assess the statistical reliability of simulation outcomes by estimating the minimum number of stochastic runs required for stable and reproducible results. The model generates 3D spatiotemporal distributions of germ-cell fate and monitors the stepwise commitment of germ cells into either selected oocytes or dying non-selected cells, giving insight into how a selected subset contributes to establishing the ovarian reserve.
