Three-dimensional visualisation of human ovarian follicles using a whole-mount immunolabelling and optical tissue clearing method.

Abstract: To more accurately classify human ovarian follicles by developing a novel methodology with three-dimensional visualisation using whole-mount immunolabelling and optical tissue clearing techniques. A whole-mount immunolabelling protocol combined with optical tissue clearing was applied to human ovarian tissue for three-dimensional follicle analysis. Key markers, including DAPI for nuclear staining, DDX4 for oocyte-specific labelling, and LAMININ for basal membranes, were used to visualise follicular structures. The tissues underwent a clearing process to enable confocal z-stack imaging to obtain detailed three-dimensional data. Ovarian cortical tissue from three paediatric patients (aged 9-12 years) who had not undergone chemotherapy treatment was collected. The tissue was dissected into small fragments and stained to identify viable follicles. Follicle and oocyte size, as well as granulosa cell size and type, were assessed across multiple dimensions (XY, XZ, YZ planes). Follicles were classified as primordial or transitional based on granulosa cell characteristics. Three-dimensional analysis across XY, XZ, and YZ planes revealed that 58% of follicles, initially classified as primordial using conventional two-dimensional methods, were misidentified as transitional due to the presence of cuboidal granulosa cells that were only detectable in multi-plane analysis. Moreover, three-dimensional analyses revealed significant differences in the number and size of cuboidal granulosa cells detected on transitional follicles. This study presents a novel whole-mount immunolabelling and optical tissue clearing methodology for accurate three-dimensional visualisation and classification of human ovarian follicles. This technique improves the accuracy of follicle staging and provides a valuable tool for future research into ovarian function, reproductive health, and conditions impacting follicle development. Lay Summary: In this study, we explored a new method for examining ovarian follicles - structures that contain the immature eggs - within human ovarian tissue. Traditional methods, which rely on two-dimensional imaging, can lead to mistakes in classifying the development of these follicles due to their spherical shape. To address this, we developed techniques to visualise the ovarian tissue in three dimensions. Using ovarian tissue from three patients, the tissue was processed using techniques called whole-mount immunolabelling (to detect structures) followed by optical clearing (to visualise the structures) and then analysed using microscopy. This enabled us to create detailed 3D images that showed the structures of the immature eggs and follicles across different planes of view. We discovered that conventional 2D assessments misclassified nearly 60% of the follicles, as certain developmental characteristics were only visible in the 3D images. This innovative approach marks the first time such detailed 3D imaging has been applied to human ovarian follicles. It not only enhances the accuracy of classifying follicle stages but also holds potential for improving fertility preservation techniques in the future. Overall, the study highlights the benefits of using modern imaging methods to gain better insights into ovarian health and development.