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  Applying label-free and 4-D imaging to quantify and track changes in lipid homeostasis in an inherited form of motor neurone disease (MND) with dementia


   Medical School

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  Dr J Chilton  No more applications being accepted  Funded PhD Project (European/UK Students Only)

About the Project

Understanding the biological basis of the dysfunctional lipid metabolism common to many neurological conditions offers an important new way to treat these devastating disorders. We will use cutting-edge four-dimensional microscopy and label-free biophysical imaging to study lipid dynamics in an inherited neurological disease, providing important insights into dementia and MND.

Mast syndrome is an inherited upper motor neurone disease associated with a rapidly-progressing form of dementia and belongs to a genetically and clinically heterogeneous group of neurodegenerative diseases; the hereditary spastic paraplegias. Due to a lack of understanding of the biological basis of these and related neurodegenerative conditions, there is currently no treatment available. Our group has a long track record in the investigation of these conditions, and has previously discovered 11 new genetic causes of these conditions, including Mast syndrome shown to be due to mutation of the ACP33 gene. Little is known about the function of ACP33 protein, although some molecular evidence suggests it may regulate axonal branching, and protein modelling suggests it binds lipids. We hypothesise that ACP33 acts as a molecular chaperone shuttling lipids throughout the elaborate, neuronal morphology.

Defective lipid homeostasis is emerging as a common theme in many neurodegenerative conditions, and better understanding of these processes would offer novel therapeutic avenues. A major barrier to studying lipid function is the difficulty labelling and visualising them. Fluorescent reporters can map localisation but may mask endogenous interactions and induce side-effects. SRS microscopy circumvents these issues by providing label-free, chemically-specific, quantitative imaging of chemical species distribution within a cell based on vibrational spectroscopy. In contrast to their unsuitability for many fluorescent applications, lipids are well-suited to SRS microscopy due to abundant C-H bonds providing a strong Raman signal. In pilot studies we have scanned the range of C-H vibrational modes to construct a high-resolution hyperspectral map of lipid distribution within individual neurons. We believe this to be the first time the chemical composition of neurons has been visualised at such detail and in a label-free manner. We have been able to identify subcellular domains enriched in lipids and – of relevance to Mast syndrome – these include sites of axon branching.

To complement SRS and monitor intraneuronal lipid transport with higher temporal resolution we will use 4-D confocal microscopy of live cells loaded with fluorescently labelled lipids and/or genetically encoded fluorescent reporters known to minimally impact endogenous systems. We will develop algorithms to track lipid vesicles and automate analysis of neuronal shape for quantitative assessment of intracellular distribution and morphological changes.

This unique combination of biophysics and 4-D image analysis applied to a genetic disorder will shed new light on the underlying pathology of Mast syndrome and provide invaluable insights for broader application to other related neurodegenerative conditions.

The research will be primarily based within the new Wellcome Wolfson Medical Research Centre at the University of Exeter Medical School (UEMS), which brings together clinical and biomedical scientists working in the fields of genomics, cell biology and human physiology and is home to >20 PhD students forming a vibrant training environment with a highly active departmental seminar program.

Academic Supervisors:

Dr John Chilton, University of Exeter Medical School: http://medicine.exeter.ac.uk/about/profiles/index.php?web_id=John_Chilton

Professor Andrew Crosby, University of Exeter Medical School: http://medicine.exeter.ac.uk/about/profiles/index.php?web_id=Andrew_Crosby

Professor Julian Moger, College of Engineering, Mathematics and Physical Sciences: http://emps.exeter.ac.uk/physics-astronomy/staff/jmoger

Dr Emma Baple, University of Exeter Medical School

Location: University of Exeter, St Luke’s Campus, Exeter



Funding Notes

This project is one of a number which are funded within the Carlota Palmer PhD programme. This four-year programme, run under the auspices of the Centre for Biomedical Modelling and Analysis, will commence in September 2016. The studentships will provide funding for a stipend (currently £16,165 per annum), research costs and UK/EU tuition fees for four years. Further details can be found here: http://www.exeter.ac.uk/bma/phd/



References

Entry requirements:
Applicants should be highly motivated and have, or expect to obtain, either a first or upper-second class BSc (or equivalent) in a relevant discipline. International applicants must also have IELTS score of 7 and above (or equivalent qualification).

How to apply:

Please apply via the application link. Please be aware you will be asked to upload the following documents:

• CV
• Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the
project.
• Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are
still studying)
• If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English
(see entry requirements above)

You will be asked to name 2 referees as part of the application process however we will not contact these people until the shortlisting stage. The closing date for applications is midnight on Monday 25th April 2016.

If you have any general enquiries about the application process please email UEMS-graduateresearch@exeter.ac.uk. Project specific queries should be directed to Dr John Chilton J.K.Chilton@exeter.ac.uk.




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