Big Data & muscle research │ Sending Worms to Space with Colleen Deane

Can computers help us understand muscle health? How are the results from Worms in Space research integrating to our Earth-based studies on people? In this episode we'll look at how computational modelling is used to analyse results from clinical trials that we have run.

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Skeletal muscle is not just regulated by a single molecule. In fact, it's much, much more complex than that. Many, many molecules within the muscle interact with each other to cause changes such as muscle loss and muscle growth and muscle disease. Some of the standard laboratory techniques that you just learnt about in the previous video only have the ability for us to look at a small number of molecules of interest.

Whilst this is helpful at telling us parts of the story, it doesn't tell us the whole story about how different molecules interact with each other to cause changes in muscle health. But this limitation can be overcome by using analytical techniques, such as RNA sequencing, which looks at all of the genetic instructions, so all of the genes within a sample, and not just a few. And this is a form of untargeted analysis.

However, such untargeted approaches produce large amounts of data, and these large amounts of data can be hard for us to handle, so we can overcome this by using computer analysis. Advances in computational technology means that we can now analyse a huge amount of biological data within seconds and minutes, which would otherwise take us years to analyse if we did it ourselves. We have recently used a particular computational approach called bioinformatics, and we use this to investigate the muscle networks regulating the ageing response to exercise.

To do this we collected muscle tissue from young and older adults before and after strenuous exercise, and we analysed all of the genes within these samples using RNA sequencing. Using specialised computer software, such as R, we were able to use these large gene data files to generate networks of muscle, which outlined which molecules interact with what other molecules. Within these networks we were then able to identify a small number of these molecules, which might be very, very important for predicting how muscles adapt to certain situations, and this includes things like ageing and exercise.

For example, our analysis identified a gene called PAX4. This gene is implicated in supporting the organelles within the muscle that are responsible for breathing, the mitochondria, and so may be a future target for investigation. This is just one example and one gene that this type of analysis has helped us identify.

Going forward, we can test the importance of these individual molecules in particular situations, such as space flight, using the worm. These findings can then be translated into humans to test the importance in health and disease on Earth.

So, have you found this series interesting? And would you like to get involved in space science research? If so, then stay tuned for our final episode in this fascinating series where we will tell you about the many ways in which you can follow up your interests. Or even, you could start a new career.

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