Francis Crick Institute

👨🏻‍🔧 Was here between March 2022 to September 2022 at the Francis Crick Institue (London, UK)

During my graduate school journey in London, I was lucky enough to join the Serio Lab. They gave me insight and direction on my Master’s project, and allowed me to do things I was interested in. This is also where my interest in python coding and data science started.

My Work.

The main goal of my research here was to optimize a platform for axonal outgrowth in cortical and spinal motor neurons in vitro. My labmates had previously developed a pipeline to do this using 3D printing and PDMS (a cell compatible polymer) to create macrofluidic devices. This would allow us to culture neurons overtime, as well as direct their axonal growth in a bidirectional manner.

One of the major problems I encountered was after data collection. The method we used at the time was to manually measure the length of randomly selected neurons. With the ten different experimental repeats, this resulted in thousands of data inputs, thus I couldn’t find an efficient method to analyse with GraphPad. To resolve this, I decided to put my first-year undergrad python skills to use. I hadn’t touched this in almost 4 years, so essentially it was completely new. But with this, I was able to learn data visualization and data analysis methods using Matplotlib and Seaborn.

Now, you are probably wondering “wow, you manually measured each axon?”. YES. We used the straight line tool in ImageJ to measure the length of each axon. Why did I not automate? I tried at the start of the project, but to no avail. I consulted fellow ImageJ experts within my college, but the amount of debris in the images made it too difficult. Then, near the end of my project, my supervisor taught me how to use CellProfiler. With this I was able to remove all the cell debris, and now have an accurate shape and length of each axon. I then used python to automate the axon measurement, reducing the measurement time by approximately 50%. Unfortunately, I didn’t have the time or resources to validate this analysis pipeline for my project, but hopefully the lab is working to use it officially as part of their analysis. 😢

Here’s a quick list of wet lab skills I learnt:

• Aseptic Cell culture (2D and 3D)
• Immunocytochemistry
• Fluorescent microscopy
• 3D printing and profilometer readings

Learning Outcomes.

I spent my first month understanding and learning lab procedures. Eventually, they let me work independently and I was off to the races. One major difference here compared to my other labs was the amount of freedom and decision-making I was allowed on the project. And with that liberty, I was able to find new methods to solve complicated problems, as well as learn new skills independently.

Another thing I noticed was the effect of collaboration in science. The institute really prided itself on its multidisciplinary collaboration, and you can really see that at all levels of research. This is something I admired and hope to see in my future work.