Establishment and characterization of steroidogenic granulosa cells expressing beta(2)-adrenergic receptor: regulation of adrenodoxin and steroidogenic acute regulatory protein by adrenergic agents

Development of an acute ovine model of polycystic ovaries to assess the effect of ovarian denervation

Introduction

Polycystic ovary syndrome (PCOS) seems to be associated with increased ovarian sympathetic nerve activity and in rodent models of PCOS reducing the sympathetic drive to the ovary, through denervation or neuromodulation, improves ovulation rate. We hypothesised that sympathetic nerves work with gonadotropins to promote development and survival of small antral follicles to develop a polycystic ovary phenotype.

Methods

Using a clinically realistic ovine model we showed a rich sympathetic innervation to the normal ovary and reinnervation after ovarian transplantation. Using needlepoint diathermy to the nerve plexus in the ovarian vascular pedicle we were able to denervate the ovary resulting in reduced intraovarian noradrenaline and tyrosine hydroxylase immunostained sympathetic nerves. We developed an acute polycystic ovary (PCO) model using gonadotrophin releasing hormone (GnRH) agonist followed infusion of follicle stimulating hormone (FSH) with increased pulsatile luteinising hormone (LH). This resulted in increased numbers of smaller antral follicles in the ovary when compared to FSH infusion suggesting a polycystic ovary.

Results

Denervation had no effect of the survival or numbers of follicles in the acute PCO model and did not impact on ovulation, follicular and luteal hormone profiles in a normal cycle.

Discussion

Although the ovary is richly inervated we did not find evidence for a role of sympathetic nerves in ovarian function or small follicle growth and survival.

Evaluating structure-based activity in a high-throughput assay for steroid biosynthesis

Data from a high-throughput human adrenocortical carcinoma assay (HT-H295R) for steroid hormone biosynthesis are available for >2000 chemicals in single concentration and 654 chemicals in multi-concentration (mc). Previously, a metric describing the effect size of a chemical on the biosynthesis of 11 hormones was derived using mc data referred to as the maximum mean Mahalanobis distance (maxmMd). However, mc HT-H295R assay data remain unavailable for many chemicals. This work leverages existing HT-H295R assay data by constructing structure-activity relationships to make predictions for data-poor chemicals, including: (1) identification of individual structural descriptors, known as ToxPrint chemotypes, associated with increased odds of affecting estrogen or androgen synthesis; (2) a random forest (RF) classifier using physicochemical property descriptors to predict HT-H295R maxmMd binary (positive or negative) outcomes; and, (3) a local approach to predict maxmMd binary outcomes using nearest neighbors (NNs) based on two types of chemical fingerprints (chemotype or Morgan). Individual chemotypes demonstrated high specificity (85-98%) for modulators of estrogen and androgen synthesis but with low sensitivity. The best RF model for maxmMd classification included 13 predicted physicochemical descriptors, yielding a balanced accuracy (BA) of 71% with only modest improvement when hundreds of structural features were added. The best two NN models for binary maxmMd prediction demonstrated BAs of 85 and 81% using chemotype and Morgan fingerprints, respectively. Using an external test set of 6302 chemicals (lacking HT-H295R data), 1241 were identified as putative estrogen and androgen modulators. Combined results across the three classification models (global RF model and two local NN models) predict that 1033 of the 6302 chemicals would be more likely to affect HT-H295R bioactivity. Together, these in silico approaches can efficiently prioritize thousands of untested chemicals for screening to further evaluate their effects on steroid biosynthesis.

Progestational effects of dydrogesterone in vitro, in vivo and on the human endometrium

Dydrogesterone has a molecular structure closely related to that of natural progesterone, but it has enhanced oral availability compared with progesterone. The hormonal profile and the progestational potency of dydrogesterone has been determined in vitro, in vivo and in humans, in combination with estrogens or without. It showed varying affinity for progesterone-binding proteins in uterine tissue in vitro, depending on the species. It exerted a clear progestational response in the rabbit in vivo, although the potency was influenced somewhat by the route of administration. When used in hormone replacement therapy, 10mg dydrogesterone given sequentially provides adequate protection against endometrial hyperplasia in postmenopausal women using 2mg estradiol. Similarly, a dydrogesterone dose of 5mg also protects the endometrium when continuously combined with 1mg estradiol. Dydrogesterone also has beneficial effects in women with amenorrhea/oligomenorrhea, dysfunctional uterine bleeding and irregular cycles. In conclusion, having a similar profile to progesterone but with better oral availability, dydrogesterone has been used successfully to treat disorders related to absolute or relative progesterone deficiency.

Ovarian granulosa cell lines

The ovary is a complex endocrine gland responsible for production of sex steroids and is the source of fertilizable ova for reproduction. It also produces various growth factors, transcription factors and cytokines that assist in the complex signaling pathways of folliculogenesis. The ovary possesses two primary steroidogenic cell types. The theca cells (and to a lesser extent, the stroma) are responsible for androgen synthesis, and the granulosa cells are responsible for conversion of androgens to estrogens, as well as progesterone synthesis. These cells undergo a transformation in the luteal phase of the menstrual cycle, converting them from estrogen producing, to predominantly progesterone producing cells. Understanding the molecular mechanisms regulating these cells is essential in understanding the regulation of steroidogenesis and reproduction. Creation of appropriate in vitro cell model systems can provide important tools for the study of ovarian function. This has led to the development of ovarian steroidogenic cell lines in several laboratories. Developing theca cell lines has met with limited success. Conversely, numerous human and animal granulosa cell lines have been developed. This review will discuss the existing granulosa cell lines and their characteristics.

Temporal and spatial patterns of ovarian gene transcription following an ovulatory dose of gonadotropin in the rat

In recent years, there have been a number of efforts to identify genes that are expressed in mature ovarian follicles in response to an ovulatory dose of LH or its homologue hCG. This review keys on 20 ovulation-specific genes that we have identified by the molecular procedure known as differential display. The objective is to use this sampling of genes to illustrate the diversity in the temporal and spatial patterns of expression of genes in the ovary following the stimulus of this gonadal target tissue by a single glycoprotein hormone. The specific genes that are surveyed include 5-aminolevulinate synthase; early growth response protein-1; gamma-glutamylcysteine synthetase; cyclooxygenase-2; epiregulin; pituitary adenylate cyclase-activating polypeptide; tumor necrosis factor-stimulated gene-6; regulator of G-protein signaling protein-2; adrenodoxin; steroidogenic acute regulatory protein; 3alpha-hydroxysteroid dehydrogenase; CD63, a disintegrin and metalloproteinase with thrombospondin motifs; tissue inhibitor of metalloproteinase-1; carbonyl reductase, a G-protein-coupled receptor; pancreatitis-associated protein-III; glutathione S-transferase; and metallothionein-1. The ovulatory expression of these different genes is predominantly within the granulosa layer of mature follicles. However, there were also instances of expression in the thecal and stromal tissue of the ovary, as well as in vascular endothelial cells and in luteal tissue. The overwhelming impression is that the molecular events of ovulation are far more complex, and therefore more highly ordered, than originally imagined.