This project proposes a multidisciplinary approach for studying the decline of vision with ageing. It focuses on a specialised monolayer of cells, the retinal pigment epithelium (RPE), which comes in direct contact with the neuroretina and separates it from the vasculature at the back of the eye. RPE cells ensure rods and cones in the retina are renewed and supplied with nutrients daily throughout life. Due to the intense metabolic rate they sustain, as well as the high levels of light and oxygen they are exposed to, RPE cells are prone to high oxidative stress. Although they are equipped to protect themselves against this stress, their protective antioxidant mechanisms decline with ageing and this contributes to the impairment of the overall RPE functions which in turn leads to gradual visual impairment and even blindness.
Understanding the mechanisms through which ageing and oxidative stress lead to changes in normal RPE physiology is essential for developing preventative and therapeutic approaches for ensuring the ageing population can retain effective eyesight. The project will make use of recent gene expression profiling of RPE cells at different ages and in response to specific age-related stresses known to induce oxidative stress. The aim is to build on this data to create and validate a comprehensive model of the modulation of RPE functional pathways affected by age-related response to oxidative stress.
The training will ensure development of highly topical skills in data science and computational modelling combined with molecular cell biology and live-cell imaging applied to in vitro cell models of RPE ageing. Specifically, training will encompass mathematical modelling/in silico analysis and transcriptome data analysis, alongside a broad range of core and advanced molecular, cell-based techniques aimed to develop key laboratory-based skills in induced pluripotent stem cells (iPSCs)/differentiated cell culture, qPCR, immunoblotting, cloning, flow cytometry and cell imaging. While primarily based in the Ocular Molecular Biology and Mechanisms of Disease Group in Liverpool (http://www.liv.ac.uk/paraoan), the student will benefit from the collaboration with the integrative bioinformatics and computational modelling group in Newcastle, developing skills that will be vital for future Biosciences research. The student will have the opportunity to attend ageing, vision and systems biology conferences benefitting from the groups’ multiple international collaborations.
We encourage students from diverse backgrounds to apply and contribute to the team’s truly inclusive, engaging and supportive culture. Candidates with either a biological and/or computational background are welcome to apply as full interdisciplinary training will be provided.
Informal enquiries are welcome and encouraged to be made to Professor Luminita Paraoan ([Email Address Removed]).
HOW TO APPLY
Applications should be made by emailing [Email Address Removed] with a CV and a covering letter, including whatever additional information you feel is pertinent to your application; you may wish to indicate, for example, why you are particularly interested in the selected project/s and at the selected University. Applications not meeting these criteria will be rejected. We will also require electronic copies of your degree certificates and transcripts.
In addition to the CV and covering letter, please email a completed copy of the Application Details Form (Word document) to [Email Address Removed] noting the additional details that are required for your application which are listed in this form. A blank copy of this form can be found at: https://www.nld-dtp.org.uk/how-apply.
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