ABSTRACT
First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Gaëlle Letort is first author on ‘ An interpretable and versatile machine learning approach for oocyte phenotyping’, published in JCS. Gaëlle conducted the research described in this article while a post-doc in Marie-Emilie Terret and Marie-Hélène Verlhac’s lab at Collège de France, Paris. She is now a Research Engineer (CNRS) in the lab of Department of Developmental and Stem Cell Biology at Institut Pasteur, Paris, investigating mathematical modelling and image analysis applied to biology.
Gaëlle Letort
How would you explain the main findings of your paper in lay terms?
From a single oocyte, a roundish cell of only hundreds of microns, an embryo can develop after fertilization by the sperm and gives rise to a whole human being. However, not all oocytes are of sufficiently good quality to develop correctly into an embryo after fertilization. Our aim was to be able to recognize as early as possible a correct oocyte, both in the context of fecondation in vitro (FIV)/in vitro fertilisation (IVF) in the clinics and for research purposes, to better understand the process. We proposed a new computational tool based on images or movies of single oocytes taken in a non-invasive manner that allows us to automatically classify and describe oocytes.
When doing the research, did you have a particular result or ‘eureka’ moment that has stuck with you?
There was not a particular striking ‘eureka’ moment in our project itself, but when my tool was used for other biological projects in the team, it always felt like small eurekas to me.
Why did you choose Journal of Cell Science for your paper?
We submitted to Journal of Cell Science through Review Commons. One motivation was that it is published by The Company of Biologists, which is a not-for-profit organization. Another one was that the scope of the journal accepts interdisciplinary works and in particular papers presenting software/pipelines. The process of transfer from Review Commons to JCS was direct and did not require additional input until the decision of the editor, which was very fast.
Movies of mouse oocyte maturation with their membrane (purple) and zona pellucida (green) automatically segmented.
Movies of mouse oocyte maturation with their membrane (purple) and zona pellucida (green) automatically segmented.
Have you had any significant mentors who have helped you beyond supervision in the lab? How was their guidance special?
I would not have stayed in academia without the mentoring I received. Beyond great supervision, Marie-Emilie Terret and Marie-Hélène Verlhac succeeded in motivating me to apply to several positions and boosted my self-confidence when I needed it. I also have to mention my PhD supervisors, Laurent Blanchoin and Manuel Théry. They have been very supportive and always ready to give me their opinions and advice all along my journey. Finally, most scientists I have collaborated with have been nice enough to also offer micro-mentoring through advice, feedback, helping with rehearsals... all these interactions have been very important.
What motivated you to pursue a career in science, and what have been the most interesting moments on the path that led you to where you are now?
I did a PhD because I was told it's a unique occasion when you can really take the time to explore a subject deeply and continue to learn, and also that it was much easier to go to industry from academia than the opposite way around. I fluctuated for several years between applying for a researcher job, a research engineer job or going for well-paid jobs; the guidance of my mentors was essential in getting me to my current position. A potentially interesting point was my choice to join wet labs, although I am totally dry (doing mathematics and computer science). I find it both very challenging and interesting to work with people that have totally different ways of thinking and scientific cultures. I enjoy how we each bring our specific complementary expertise (biology or mathematics) together to tackle a biological question. This synergy of expertise shows the importance of collaborative and interdisciplinary works, which are not yet very well adapted and rewarded in the current academic system in my opinion.
Who are your role models in science? Why?
There are plenty of scientists whose work I admire, but for me what makes role models is their behaviour over their scientific production. I enjoy listening to scientists who are passionate about their projects; it's a source of motivation. I consider as role models scientists that participate in creating a better academic culture, e.g. by simply being nice to others, promoting team work over individual achievement, fighting against gender and racial systemic biases, contributing to open science… More importantly, I am very inspired by all the scientists that are making drastic efforts to make research more sustainable or to find solutions to fight the climate crisis. It's difficult but necessary and they are clearly models for me.
“I am very inspired by all the scientists that are making drastic efforts to make research more sustainable or to find solutions to fight the climate crisis.”
What's next for you?
I am now a Research Engineer in image analysis and mathematical modelling for the Department of Developmental and Stem Cell Biology at Institut Pasteur.
Gaëlle Letort's contact details: Institut Pasteur, 25 rue du docteur Roux, 75015 Paris, France
E-mail: [email protected]
