Sharing new non-invasive circadian phenotyping methods

This project will transfer expertise in two new refined methods of studying mouse physiology and behaviour developed in Oxford to a network of collaborators based in Berlin. Our lab has established and validated new non-invasive approaches to assess sleep and body temperature in laboratory mice. These methods provide major welfare refinements in comparison with existing invasive methods.

In this project we will share our expertise with these new methods with collaborators in Berlin. By establishing these techniques in a central facility, this will benefit five separate circadian research groups working on a range of different mouse models, including neuropsychiatry, immunology, oncology and RNA biochemistry.

To enable our collaborators to use these methods, we will run a series of hands-on workshops in Oxford, where end-users will learn how these systems work, see them in action, and build their own systems from scratch. Attendees will also learn how to analyse the data obtained from these systems. These workshops will enable attendees to set these systems up in their own lab, encouraging the wider use of these methods in the circadian community. Moreover, they will provide an ideal opportunity to develop a range of online training material to enable the wider community to more easily implement these methods.

Finally, we will work with mathematical experts in circadian data analysis to improve our data analysis pipelines, with a particular focus on the detection of circadian disruption - a hallmark of many disorders. We will also encourage clearly annotated behavioural data deposition, which will improve transparency and reproducibility of circadian studies. This will provide a major resource to this user community, enabling data sharing to reduce - and in some cases even replace - the use of new animals.

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Skills and Knowledge Transfer grant

Status:

Not yet active

Principal investigator

Professor Stuart Peirson

Institution

University of Oxford

Grant reference number

NC/V000977/1

Award date:

Jun 2020 - May 2022

Grant amount

£35,120