Cenk Gurdap

I am interested in using the strengths of different techniques to develop cutting-edge methods to rule out some of the challenges in the field and identify the biophysical properties of cells or crucial biomolecules.

* 2023-now PhD student, SciLifeLab, Karolinska Institutet, Stockholm, Sweden
* 2020-2022 MSc in Molecular Techniques in Life Science, Karolinska Institutet-
KTH Royal Institute of Technology-Stockholm University, Stockholm, Sweden
* 2015-2020 BSc in Biology, Middle East Technical University, Ankara, Turkey

Physical remodeling of our cells as a response to environmental changes is essential for their survival and function [1]. The ability of immune cells to pass through tight epithelial cell layers from circulating blood during infection [2], the ability of tumor cells to travel throughout the body during metastasis [3], migration potential of the cells after epithelial-to-mesenchymal transition [4] could be examples where cells undergo extensive remodeling. Although numerous studies aimed at finding protein markers during these key steps, there is a major gap in our understanding of how collective biophysical properties of the cells (such as stiffness, fluidity, and viscosity) alter during these crucial biological processes. Similarly, our understanding of how the biophysical properties of cells change in diseases is extremely limited. To gain a thorough mechanistic perception of cellular processes and diseases, it is essential to fill this gap and have a clear and quantitative picture of the biophysical remodeling of the cells during these processes. It is becoming clearer that biophysical principles can serve as the “cause” of many cellular processes rather than being only passive “consequences” [5, 6]. Moreover, biophysical properties can vary without notable changes in protein or RNA levels. Therefore, these physical properties can be exploited as complementary to the current protein or nucleic acid markers to diagnose and treat diseases. Current biophysical technologies suffer from low sampling (one cell at a time), which is a major obstacle to apply them to medical problems that require measuring thousands of cells [7-9]. This bottleneck can only be overcome with high throughput methodologies that can robustly measure the biophysical properties.

I aim to develop an imaging and cytometry pipeline (from optics to high throughput analysis) to map the collective biophysical properties of cells that are distinct in different cell types, states (e.g., young vs. old), and diseases (e.g., dyslipidemia). This will potentially pave the way for using biophysical properties for the prediction of disease phenotypes as a complementary aspect to current protein or nucleic acid markers.

References:
1) Ruprecht, V. et al. J Cell Sci 130, 51-61 (2017).
2) Escribano, J. et al. PLoS computational biology 15, e1006395 (2019).
3) Suresh, S. Acta biomaterialia 3, 413-438 (2007).

4) Margaron, Y. et al. bioRxiv, 797654 (2019).

5) James, J. R. &

6) Bizzarri, M. et al. Nature reviews. Molecular cell biology 20, 261-262 (2019).

7) Sezgin, E. et al. Biophys J 113, 1321-1330 (2017).

8) Sezgin, E. et al. Chemphyschem 16, 1387-1394 (2015).
9) Sezgin, E. et al. Nature Protocols (2019).