Georgios Pavlou

Georgios obtained his Bachelor’s degree in Mathematics from the University of Crete in Greece. He then followed two master programs in United Kingdom (University of Aberdeen) and France (Paris Descartes University) where he became more familiar with the field of biology and biophysics. He has obtained his PhD from the University of Grenoble Alpes/UGA in the laboratory of Isabelle Tardieux at the Institute for Advanced Biosciences (CNRS, INSERM, UGA) in Grenoble, where he gained knowledge and experience on interdisciplinary topics at the interface between cell biology, biophysics and parasitology.

Can you describe in a few words your research work? And the project and experiments for which you wanted to use PRIMO?

« The main interest of the Tardieux’s laboratory and my PhD project is to decipher how forces drive the unique motile and invasive capacities of the single-celled eukaryotic parasite Toxoplasma gondii. This highly polarized cell uses a super fast gliding motility mode that remains largely elusive. To gain insights on this motility mode, I used fast live imaging combined with traction force microscopy (TFM) and reflection interference contrast microscopy (RICM) benefiting from the IT collaborative teams at the LiPhy Institute in Grenoble. I was able to uncover that the parasite glides by coupling polar adhesions and de-adhesion with traction and dragging forces. The PRIMO technique was needed to create composite patterns with a non-adhesive area next to an adhesive one with the crucial request of a sharp demarcation. Indeed, we wanted to selectively impede the Toxoplasma front adhesion without compromising the rear one when it approached the edge. Thanks to the accuracy of the pattern and despite the Toxoplasma few micron size, we were able to demonstrate the strict request of the front polar adhesion for traction force to operate and forward motility to proceed. »

Time lapse of Toxoplasma gondii tachyzoites on PEG-Fibronectin composite accurate micropattern – generated with the PRIMO system from Alvéole – to assess the adhesion requirement for forward gliding. Results: The tachyzoite must apically adhere to fibronectin to undergo helical gliding. When it encounters a PEG area, it becomes unable to move forward because it can not build the required apical contact. Pavlou et al., ACS Nano, 2020.

What made you choose PRIMO ?

« Advertisement about the accuracy of the technique at the ASCB conference in San Diego, California. »

Which solution did you use before using PRIMO?

« I made patterns using glass mask micropatterning protocols and the problem was that I could never achieve a clear demarcation between the pattern and the non-adhesive area. There were always some proteins (i.e. fibronectin) outside of the pattern area but even very few were enough to prevent robust conclusion on the parasite adhesion requirements for helical gliding motility. »

If you were to describe PRIMO in one word, what would it be?

« Precision »

And finally, how would you qualify the support provided by the team?

« It has been one of the best experience I had during my PhD time in terms of collaboration. The Alvéole team was always helpful and highly reactive in the design of the pattern that we were interested. They also guided and advised me when I encountered some technical problems, and they were generous in making new patterns to solve these issues. In addition, the success came since I was able to use the patterns and provide compelling evidence that significantly strengthened our study on Toxoplasma motile forces. »

Find out more on this research work from Georgios Pavlou and Isabelle Tardieux :

• Pavlou G, Touquet B, Vigetti L, Renesto P, Bougdour A, Debarre D, Balland M, Tardieux I.  Coupling Polar Adhesion with Traction, Spring, and Torque Forces Allows High-Speed Helical Migration of the Protozoan Parasite Toxoplasma. ACS Nano. 2020 Jun 1. doi: 10.1021/acsnano.0c01893. https://pubs.acs.org/doi/10.1021/acsnano.0c01893
• Highlight by American Society of Chemistry: https://www.youtube.com/playlist?list=PLLG7h7fPoH8JRH8bEJdgnwZnyA5N-9UaE