Optimising an Encapsulated In Vitro Follicle Growth System to Evaluate the Impacts of Cholesterol on Follicle Development

<p><strong>Encapsulated in vitro follicle growth (eIVFG) is a 3D culture method that can be used to culture ovarian follicles. For this thesis, a protocol utilising an alginate hydrogel to encapsulate follicles was adapted for use in our lab to study and follow follicle growth, or folliculogenesis.</strong></p><p>The overall objective of this thesis was to investigate the hypothesis that increased cholesterol within in vitro follicle culture media would negatively impact follicle development. To answer the hypothesis, an eIVFG protocol had to be optimised to study follicular growth in vitro. Several parameters (follicle collected method, media pH, alginate viscosity and concentration) were optimised and baseline values for eIVFG including 17β-estradiol and progesterone concentrations, expression of key genes in the oocyte and markers of apoptosis (Gdf9, Bmp15, Bax and Bcl2), and measures of follicle health and growth were evaluated. Once these values were established, follicles were cultured in three conditions based on known differences in circulating cholesterol in individuals classified as having different levels of adiposity: high-body fat (high cholesterol), low-body fat (low cholesterol) and a control condition. It was established that there was no significant impact of any of the three conditions on follicle growth, nor any significant difference in other markers of follicle health such as antrum formation or follicle survival, or on the expression of Gdf9, Bmp15, Bax or Bcl2. However, there were higher 17β-estradiol levels in high-body fat conditions than both low-body fat or control conditions.</p><p>Overall, this thesis found that increased cholesterol did not negatively impact follicle growth, and this, along with the optimised eIVFG protocol, will contribute to future studies on the impact of circulating lipids, such as cholesterol, on folliculogenesis. In time, the eIVFG system can also be used to understand how variations in conditions could impact outcomes of assisted reproductive technologies.</p>