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PhD Studentship - Pituitary Plasticity Induced by Chronic Stress

University of Exeter - University of Exeter Medical School

Qualification Type: PhD
Location: Exeter
Funding for: UK Students, EU Students
Funding amount: £14,777
Hours: Full Time
Placed On: 1st October 2018
Closes: 23rd November 2018
Reference: 3229
 

Lead Supervisor: 
Dr Joel Tabak, University of Exeter Medical School

Additional Supervisors: 
Dr Jamie Walker, Department of Mathematics, University of Exeter 
Professor Stafford Lightman, University of Bristol 

Project Details

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 cardiff.onlinesurveys.ac.uk/gw4-biomed-mrc-dtp-student-2019 by 5pm Friday 23 November 2018.

Funding Details

Full UK/EU tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£14,777 for 2018/19, updated each year) for 3.5 years.

Funding Comment

This studentship is funded through GW4 BioMed MRC Doctoral Training Partnership. It consists of full UK/EU tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£14,777 for 2018/19, updated each year) for 3.5 years.

   
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