Our research interests focus on
1) quantifying spatial and temporal dynamics of proteins during cell migration,
2) characterizing metabolic alterations in cells and tissues and
3) developing novel imaging technologies.
Cell migration is vital for embryonic development, wound healing, and cancer metastasis. We are using the cutting edge biophysical tools to monitor molecular interactions in live cells and how their activity in spatial locations mediates cell migration. Using the raster image correlation spectroscopy (RICS) method and the Number and Molecular Brightness (N&B) analysis we have revealed the dynamic assembly and disassembly of focal adhesions as well as determined the aggregation and stoichimonetry of protein interaction. In particular we are investigating tumor invasion and executing a strategy to monitor signaling for cells migrating in 3D matrices and in tissues.
RICS along a line from the nano-scale precise imaging by rapid beam oscillation (nSPIRO) method. The orbit in this example is not smooth and only along one position along the cell protrusion. The intensity is plotted as a function of time and the time segments are cut into short time intervals or frames. The fluorescence intensities are correlated along the x and y axis as a function of time and space.
Current Project in the lab: We are are addressing specific questions in each of these areas to quantitatively access: protein interactions, changes in energy metabolism or map molecular mobility and paths that proteins follow in the nucleus and cytosol in quest finding binding and enzymatic action sites.
- Spatio-temporal regulation of p53 upon DNA induced damage.
- Huntington disease: Alterations of energy metabolism in drosophila eye disc models.
- Molecular mobility and diffusion tensor mapping of DNA repair proteins.
Though NIH’s Big Data to Knowledge (BD2K) grant,we have established a national short course in Big Data Image Processing & Analysis (BigDIPA) course intended to increase the number and overall skills of competent research scientists now encountering large, complex image data sources derived from cutting edge biological/biomedical research approaches. The course will be offered in September 2017 (click here to go to the Course Website).