Pituitary plasticity induced by chronic stress. Medical Sciences, PhD (GW4 BioMed MRC DTP)

Supervisory team:
Dr Joel Tabak, University of Exeter Medical School
Dr Jamie Walker, Department of Mathematics, University of Exeter
Professor Stafford Lightman, University of Bristol

Project description:
The stress response is mediated by a neuroendocrine system consisting of the brain, pituitary, and adrenal glands. Repeated activation of this system can lead to “chronic stress” with altered message from the brain to the pituitary. This project aims to understand how the pituitary adapts its response to repeated stress in order to reverse it.

Neuroendocrine responses to stress are coordinated by corticotroph cells of the anterior pituitary. These cells receive messages from the hypothalamus, and their interaction with the adrenals is key in generating healthy levels of glucocorticoids. In chronic stress, pituitary corticotrophs receive a different mix of peptides from the hypothalamus, compared to healthy conditions. Yet, there are no studies examining how pituitary corticotroph cells adapt to repeated stress conditions.

The change in composition of hypothalamic peptides seen by corticotrophs in chronic stress changes the amount of receptors to these peptides. We hypothesize that the resulting changes in activity will also change the expression of ion channels that control corticotroph electrical activity. As a result of this activity-dependent plasticity, different corticotroph subpopulations may be expressed in the pituitary.

To understand the chronic stress-induced plasticity of pituitary corticotroph cells, we will use a multidisciplinary combination of approaches: sequencing and machine learning to define corticotroph subpopulations; electrophysiology and mathematical modelling to test how plasticity affects corticotroph activity and how it can be reversed.

Aim 1: Determine the relationship between ion channel expression levels and receptor expression levels in pituitary corticotrophs of healthy rats. We will determine the expression levels for receptors to hypothalamic peptides vasopressin and corticotrophin-releasing hormone and for ion channels in 500 individual corticotroph cells using RNA sequencing. Using this data set we will use unsupervised machine learning tools to determine relationships between expression levels across cells and classify corticotroph cells into subpopulations.

Aim 2: Determine the relationship between ion channel expression levels and receptor expression levels in pituitary corticotrophs of chronically stressed rats. We will repeat RNAseq and subsequent analysis in 500 corticotrophs from rats chronically stressed by adjuvant-induced arthritis. Comparing results from the control and chronic stress data sets will reveal how chronic stress alters corticotroph cell populations, and reveal which ion channels have plastic expression.

Aim 3: Determine how changes in ion channel and receptor expression in chronic stress result in altered corticotroph cell dynamic activity. We will record electrical activity and perform RNAseq on individual corticotrophs to determine how changes in expression levels translate to altered electrical activity in chronic stress. Once the most determinant changes in ion channel expression in chronic stress are identified, we will attempt to reverse them using the dynamic clamp technique.

This technique allows to add or subtract a mathematical model of an ion channel current into a live cell. Doing so, we will identify potential targets to reverse the effects of chronic stress at the pituitary corticotroph.

To apply for this project, please complete the application form at https://cardiff.onlinesurveys.ac.uk/gw4-biomed-mrc-dtp-student-2019 by 5pm Friday 23 November 2018.