Ovary Development: Insights From a Three-Dimensional Imaging Revolution

OoCount: A Machine-Learning Based Approach to Mouse Ovarian Follicle Counting and Classification

The number and distribution of ovarian follicles in each growth stage provides a reliable readout of ovarian health and function. Leveraging techniques for three-dimensional (3D) imaging of ovaries in toto has the potential to uncover total, accurate ovarian follicle counts. However, because of the size and holistic nature of these images, counting oocytes is time consuming and difficult. The advent of deep-learning algorithms has allowed for the rapid development of ultra-fast, automated methods to analyze microscopy images. In recent years, these pipelines have become more user-friendly and accessible to non-specialists. We used these tools to create OoCount, a high-throughput, open-source method for automatic oocyte segmentation and classification from fluorescent 3D microscopy images of whole mouse ovaries using a deep-learning convolutional neural network (CNN) based approach. We developed a fast tissue-clearing and spinning disk confocal-based imaging protocol to obtain 3D images of whole mount perinatal and adult mouse ovaries. Fluorescently labeled oocytes from 3D images of ovaries were manually annotated in Napari to develop a machine learning training dataset. This dataset was used to retrain StarDist using a CNN within DL4MicEverywhere to automatically label all oocytes in the ovary. In a second phase, we utilize Accelerated Pixel and Object Classification, a Napari plugin, to classify labeled oocytes and sort them into growth stages. Here, we provide an end-to-end protocol for producing high-quality 3D images of the perinatal and adult mouse ovary, obtaining follicle counts and staging. We also demonstrate how to customize OoCount to fit images produced in any lab. Using OoCount, we can obtain accurate counts of oocytes in each growth stage in the perinatal and adult ovary, improving our ability to study ovarian function and fertility.

Summary sentence

This protocol introduces OoCount, a high-throughput, open-source method for automatic oocyte segmentation and classification from fluorescent 3D microscopy images of whole mouse ovaries using a machine learning-based approach.

Rescue of follicle development after oocyte-induced ovary dysfunction and infertility in a model of POI

The mechanisms and aetiology underlying the development of premature ovarian insufficiency (POI) are poorly understood. However, the oocyte clearly has a role as demonstrated by the Double Mutant (DM) mouse model where ovarian dysfunction (6 weeks) is followed by POI (3 months) due to oocyte-specific deletion of complex and hybrid N- and O-glycans. The ovaries of DM mice contain more primary follicles (3a stage) accompanied by fewer developing follicles, indicating a block in follicle development. To investigate this block, we first analysed early follicle development in postnatal (8-day), pre-pubertal (3-week) and post-pubertal (6-week and 3-month) DM (C1galt1 F/F Mgat1 F/F:ZP3Cre) and Control (C1galt1 F/F Mgat1 F/F) mice. Second, we investigated if transplantation of DM ovaries into a "normal" endocrine environment would restore follicle development. Third, we determined if replacing DM ovarian somatic cells would rescue development of DM oocytes. At 3-week, DM primary 3a follicles contain large oocytes accompanied by early development of a second GC layer and increased GC proliferation. At 6-week, DM primary 3a follicles contain abnormally large oocytes, accompanied with decreased GC proliferation. Transplantation of DM ovaries into a 'normal' endocrine environment did not restore normal follicle development. However, replacing somatic cells by generating reaggregated ovaries (ROs) did enable follicle development to progress and thus highlighted intra-ovarian factors were responsible for the onset of POI in DM females. Thus, these studies demonstrate oocyte-initiated altered communication between GCs and oocytes results in abnormal primary follicles which fail to progress and leads to POI.

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of ovaries

Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress in recent years and has become much more accessible to non-specialists with the development of ready-to-use tools. The study of oogenesis mechanisms and female reproductive success has also recently benefited from the development of efficient protocols for three-dimensional (3D) imaging of ovaries. Such datasets have a great potential for generating new quantitative data but are, however, complex to analyze due to the lack of efficient workflows for 3D image analysis. Here, we have integrated two existing open-source DL tools, Noise2Void and Cellpose, into an analysis pipeline dedicated to 3D follicular content analysis, which is available on Fiji. Our pipeline was developed on larvae and adult medaka ovaries but was also successfully applied to different types of ovaries (trout, zebrafish and mouse). Image enhancement, Cellpose segmentation and post-processing of labels enabled automatic and accurate quantification of these 3D images, which exhibited irregular fluorescent staining, low autofluorescence signal or heterogeneous follicles sizes. In the future, this pipeline will be useful for extensive cellular phenotyping in fish or mammals for developmental or toxicology studies.

Integration of mouse ovary morphogenesis with developmental dynamics of the oviduct, ovarian ligaments, and rete ovarii

Morphogenetic events during the development of the fetal ovary are crucial to the establishment of female fertility. However, the effects of structural rearrangements of the ovary and surrounding reproductive tissues on ovary morphogenesis remain largely uncharacterized. Using tissue clearing and lightsheet microscopy, we found that ovary folding correlated with regionalization into cortex and medulla. Relocation of the oviduct to the ventral aspect of the ovary led to ovary encapsulation, and mutual attachment of the ovary and oviduct to the cranial suspensory ligament likely triggered ovary folding. During this process, the rete ovarii (RO) elaborated into a convoluted tubular structure extending from the ovary into the ovarian capsule. Using genetic mouse models in which the oviduct and RO are perturbed, we found the oviduct is required for ovary encapsulation. This study reveals novel relationships among the ovary and surrounding tissues and paves the way for functional investigation of the relationship between architecture and differentiation of the mammalian ovary.

Considerations for and against dosing rodent pups before 7 days of age in juvenile toxicology studies

This review focuses on preweaning ontogenic and developmental processes that can influence the selection of the appropriate age at which to start dosing rodent pups in juvenile animal studies (JAS). The ICH S11 guideline on 'Nonclinical Safety Testing in Support of Development of Paediatric Medicines' highlights the need to adapt the age from which animals are dosed according to the stage of development in the target organs/tissues of concern in the youngest pediatric patients. Rodents (rat or mouse) are the most common species for JAS. Despite previous practices, based on comparative ontogeny, it is rarely necessary to dose rodents younger than one week of age since postnatal day (PND)7 is appropriate to address concern for the vast majority of organs. In exceptional cases, earlier dosing (e.g., PND4) can be appropriate to address specific concern in preterm neonates and when a tissue of concern has a particularly early developmental trajectory in the rodent compared to humans. The comparative development of the CNS is particularly complex. While exposure of rodents from PND10 covers most CNS development stages relevant to human neonates, a later dosing start (yet, not later than PND14) can sometimes be appropriate to reflect specific aspects (e.g., transformation of GABAergic transmission). An extended study design including subsets of several ages can be helpful to address multiple concerns within a preweaning JAS. Such design can allow for individual assessment of each concern, whilst minimizing (potentially irrelevant) signals from tissues exposed at a developmental stage that do not match the human situation.

Unlaid Eggs: Ovarian Damage after Low-Dose Radiation

The total body irradiation of lymphomas and co-irradiation in the treatment of adjacent solid tumors can lead to a reduced ovarian function, premature ovarian insufficiency, and menopause. A small number of studies has assessed the radiation-induced damage of primordial follicles in animal models and humans. Studies are emerging that evaluate radiation-induced damage to the surrounding ovarian tissue including stromal and immune cells. We reviewed basic laboratory work to assess the current state of knowledge and to establish an experimental setting for further studies in animals and humans. The experimental approaches were mostly performed using mouse models. Most studies relied on single doses as high as 1 Gy, which is considered to cause severe damage to the ovary. Changes in the ovarian reserve were related to the primordial follicle count, providing reproducible evidence that radiation with 1 Gy leads to a significant depletion. Radiation with 0.1 Gy mostly did not show an effect on the primordial follicles. Fewer data exist on the effects of radiation on the ovarian microenvironment including theca-interstitial, immune, endothelial, and smooth muscle cells. We concluded that a mouse model would provide the most reliable model to study the effects of low-dose radiation. Furthermore, both immunohistochemistry and fluorescence-activated cell sorting (FACS) analyses were valuable to analyze not only the germ cells but also the ovarian microenvironment.

Aging conundrum: A perspective for ovarian aging

Progressive loss of physiological integrity and accumulation of degenerative changes leading to functional impairment and increased susceptibility to diseases are the main features of aging. The ovary, the key organ that maintains female reproductive and endocrine function, enters aging earlier and faster than other organs and has attracted extensive attention from society. Ovarian aging is mainly characterized by the progressive decline in the number and quality of oocytes, the regulatory mechanisms of which have yet to be systematically elucidated. This review discusses the hallmarks of aging to further highlight the main characteristics of ovarian aging and attempt to explore its clinical symptoms and underlying mechanisms. Finally, the intervention strategies related to aging are elaborated, especially the potential role of stem cells and cryopreservation of embryos, oocytes, or ovarian tissue in the delay of ovarian aging.

Effects of P4 Antagonist RU486 on VEGF and Its Receptors' Signaling during the In Vivo Transition from the Preovulatory to Periovulatory Phase of Ovarian Follicles

The development of an adequate blood vessel network is crucial for the accomplishment of ovarian follicle growth and ovulation, which is necessary to support the proliferative and endocrine functions of the follicular cells. Although the Vascular Endothelial Growth Factor (VEGF) through gonadotropins guides ovarian angiogenesis, the role exerted by the switch on of Progesterone (P4) during the periovulatory phase remains to be clarified. The present research aimed to investigate in vivo VEGF-mediated mechanisms by inducing the development of periovulatory follicles using a pharmacologically validated synchronization treatment carried out in presence or absence of P4 receptor antagonist RU486. Spatio-temporal expression profiles of VEGF, FLT1, and FLK1 receptors and the two major MAPK/ERKs and PI3K/AKT downstream pathways were analyzed on granulosa and on theca compartment. For the first time, the results demonstrated that in vivo administration of P4 antagonist RU486 inhibits follicular VEGF receptors' signaling mainly acting on the theca layer by downregulating the activation of ERKs and AKTs. Under the effect of RU486, periovulatory follicles' microarchitecture did not move towards the periovulatory stage. The present evidence provides new insights on P4 in vivo biological effects in driving vascular and tissue remodeling during the periovulatory phase.