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Developing approaches to define the ultrastructure of extracellular matrices rich in hyaluronan – key players in inflammation and reproductive biology

Project Description

Extracellular matrix (ECM) is found around and between virtually every cell in our bodies and it is this substance that organises cells into organs and provides our tissues with their particular mechanical properties. The polysaccharide hyaluronan (HA) is a ubiquitous matrix component with important roles in many physiological (e.g. in development, reproduction, inflammation and neuronal plasticity) and pathological (e.g. cancer and fibrosis) processes.
Although HA is known to play a wide range of roles in health and disease, how it does this is not well understood. Despite HA being large, it is a very simple molecule, making it intriguing to understand how HA can contribute to such diverse functions. Evidence strongly suggests that the explanation lies in the association of HA with proteins; however, it is not clear exactly how this occurs in molecular terms.
The aim of this project is to develop methods to visualise how proteins are organised within HA-rich matrices. The approach of choice is cryo-electron microscopy (Nobel Prize 2017) correlated with light microscopy. Students are encouraged to contact the supervisors for more information on this project.

Funding Notes

White Rose BBSRC Doctoral Training Partnership in Mechanistic Biology
4 year fully-funded programme of integrated research and skills training, starting Oct 2020:
• Research Council Stipend
• UK/EU Tuition Fees
• Conference and research funding

At least a 2:1 honours degree or equivalent. We welcome students with backgrounds in biological, chemical or physical sciences, or mathematical backgrounds with an interest in biological questions.

EU candidates require 3 years of UK residency to receive full studentship

Not all projects will be funded; the DTP will appoint a limited number of candidates via a competitive process.

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How good is research at University of Leeds in Biological Sciences?

FTE Category A staff submitted: 60.90

Research output data provided by the Research Excellence Framework (REF)

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