Cells within tissues function as interconnected communities. Their intra- and intercellular behaviors are manifested through the biomechanical and biophysical properties at cellular interfaces. Traditionally, these properties have been investigated using laser ablation, which involves using a pulsed laser akin to a scissor to cut the cell interfaces and then measuring the resultant responses. However, this method's invasive nature precludes continuous tracking of biomechanical properties over both space and time.
Here we propose an image-based, non-invasive technique named Tension by Transverse Fluctuation (TFlux). TFlux quantifies the transverse fluctuations along the cell-cell interface to deduce the mechanical state, enabling spatially and temporally resolved analyses at both cellular and subcellular levels. Our preliminary work with TFlux has revealed an inverse relationship between cellular tension and transverse fluctuation, alongside notable subcellular heterogeneity. We hypothesize this heterogeneity is linked to local mechanical phenomena, such as subcellular contraction and adhesion.
The underlying biophysical characteristics of these interfaces and the origins of transverse fluctuations remain largely unexplored. A particularly promising avenue of investigation involves analyzing these fluctuations in the frequency domain to uncover information previously obscured.
This approach holds immense potential for application across various biological systems. We are offering an undergraduate research opportunity to join this exciting project under the guidance of Dr. José Alvarado at the University of Texas at Austin and Dr. Shinuo Weng at Johns Hopkins University. Interested candidates should contact Dr. José Alvarado (alv@chaos.utexas.edu).
Skills required:
- Proficiency in programming (Python or equivalent)
Skills preferable but not required, but will train:
- Image analysis (scikit-image or equivalent)
- Fourier transforms
Flexible
The data has already been collected and we have a bank of microscope images of cell junctions. You will write and develop image analysis code to study junction fluctuations in frequency space.