First person – Timothy Wong and Ismail Khater

Timothy Wong

How would you explain the main findings of your paper in lay terms?

T.W. and I.K.: In this study, we develop a pipeline called SuperResNET to analyze data from super-resolution microscopy, which can visualize structures at resolutions under 20 nm. SuperResNET is a powerful analysis tool that turns complex microscope data into clear visuals and detailed, quantifiable information about protein clusters, enabling more effective classification and study of these clusters. Endocytosis is a process in which cells internalize substances from their surroundings. Clathrin protein clusters form clathrin-coated pits and vesicles that are crucial for this process. To demonstrate the capabilities of SuperResNET, we investigate how different small-molecule drugs – pitstop 2, dynasore, and latrunculin A, known inhibitors of clathrin-mediated endocytosis – affect the shape of clathrin-coated pits.

SuperResNET detects changes in the shape and size of clathrin pit structures when pitstop 2, dynasore or latrunculin A are added to HeLa cells. Pitstop 2 induces smaller, more stretched-out pits, whereas dynasore leads to rounder, more complete structures. In contrast, latrunculin A, which inhibits endocytosis by breaking down the actin cytoskeleton, induces large, heterogeneous clathrin structures. These findings suggest that pitstop 2 and dynasore stop endocytosis at different stages. This suggests that pitstop 2 specifically affects early stages of clathrin pit formation, providing a method for identifying how small molecules alter specific cellular structures directly inside cells.

Were there any specific challenges associated with this project? If so, how did you overcome them?

T.W.: One challenge in this paper was bridging biology research with computer science analysis. To tackle this, I learned some coding in R and MATLAB, which helped with putting together this paper. Coming from a biology background, learning to code and analyze data has been very interesting and will definitely be a helpful skill for doing biology research in the future.

I.K.: This project presented several challenges, primarily due to working in a new interdisciplinary field combining machine learning with biological data analysis. One of the major difficulties was handling and analyzing large-scale single-molecule localization microscopy (SMLM) data, which involved processing hundreds of thousands of clathrin localizations within a single cell. Processing and denoising SMLM data was particularly challenging, as noise filtering and segmentation were complex due to the lack of a well-defined ground truth. Additionally, validating our biological results was difficult given that we relied on simulations for comparison.

To overcome these challenges, we developed SuperResNET, a software tool that incorporates tailored computational methods for noise reduction and segmentation while leveraging network/graph analysis, statistical modeling and machine learning techniques. We also employed extensive simulation-based validation to ensure the reliability of our biological interpretations. Collaborative efforts with domain experts in biology helped refine our approaches and improved the accuracy of our analysis.

When doing the research, did you have a particular result or ‘eureka’ moment that has stuck with you?

Ismail Khater

T.W. and I.K.: One standout moment was applying SuperResNET to analyze clathrin data imaged with the MINFLUX microscope. The results were astonishing compared to what had been published previously. SuperResNET could distinctly extract, quantify and visualize each individual clathrin pits, showcasing their unique shapes and features unlike anything seen before. This advancement allowed us to better describe the changes in the clathrin pits we observed.

Why did you choose Journal of Cell Science for your paper?

T.W. and I.K.: We aim to introduce scientists to SuperResNET, a tool we developed for analyzing and visualizing super-resolution SMLM data. We believe SuperResNET is highly valuable for scientists looking to analyze their single molecule microscopy data with greater detail and in a quantifiable manner. Journal of Cell Science is read by many cell biologists, making it an ideal platform to reach researchers who would benefit from using this tool.

Have you had any significant mentors who have helped you beyond supervision in the lab? How was their guidance special?

I.K.: I have been fortunate to have two exceptional mentors who have supported me far beyond lab supervision: Dr Ghassan Hamarneh, my PhD supervisor, and Dr Ivan Robert Nabi, my PhD co-advisor and collaborator. Their guidance has been invaluable, shaping not only my research but also my personal and professional development. Beyond providing insightful advice on projects, they have shared their experiences in work, research and life, offering perspectives that extend well beyond academic guidance. Their encouragement has been instrumental in helping me pursue my research interests with confidence and independence. I am especially grateful for their trust, which has motivated me to take on new challenges and grow as a researcher.

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?

T.W.: I've been fascinated by the complexities of cell and cancer biology since high school. A memorable moment for me was looking through the eyepiece of a fluorescence microscope and clearly seeing the cell details I had labeled. Later, using a super-resolution microscope for the first time was a mind-blowing experience, and I was amazed by the incredible level of detail it could produce.

I.K.: My motivation to pursue a career in science stems from my passion for discovering new things, working collaboratively and continuously learning. I find immense joy in exploring ideas beyond my primary field, engaging with researchers from different disciplines and exchanging knowledge to drive innovation.

One of the most exciting aspects of my journey has been the opportunity to collaborate with scientists from various institutions. Learning from experts in different domains has expanded my perspective and deepened my understanding of complex problems. These interdisciplinary interactions have not only enriched my research but have also reinforced my belief in the power of collaboration to push scientific boundaries.

What's next for you?

T.W.: I will be defending my PhD soon and will then stay at the Nabi lab for a brief post-doc. Afterwards, I plan to seek a post-doctorate position in a lab specializing in fluorescence imaging, perhaps one using advanced microscopes, such as MINFLUX or lattice light-sheet microscopy. If any principal investigators are looking for a postdoctoral researcher and are interested in our work presented in our paper, please feel free to reach out to me!