Live cell imaging: understanding life and its processes by microscopy
All that life has to offer in function and diversity has a basis in how different cells and their components work together. The genetic information of the cell, DNA, provides a crucial template for all this, and any damage to this coded information can be detrimental to the organism.
What is the goal of our research?
Our broad interest lies at the heart of understanding how the cell responds to DNA damage. The cell has the ability to harness many DNA repair pathways, depending on the type of damage, and understanding them in detail opens doors to understanding diseases when the pathways malfunction.
What tools do we use?
The bacterium E. coli is our experimental workhorse, involving genetic engineering and molecular biology. We use live cell, widefield fluorescence, confocal and super-resolution microscopy approaches to address our research. Interpreting such data relies on in-house and open source algorithms. In summary, in an interdisciplinary fashion we apply principles of physics to unravel biological mechanisms.
What is the significance to society of what we do?
Antibiotic drug targets: With antibiotic resistance becoming a global phenomenon, our work on understanding bacterial replication and repair provides essential knowledge for the future / DNA repair and cancer: We enhance fundamental knowledge of DNA replication, errors in which are linked to the development of cancer / Data analysis:We develop novel analyses and algorithms to understand biological processes.
What will your specific project look like?
We are looking for student colleague(s) interested in exploring how ‘accessory helicases’ function in the cell. While understood superficially so far, these helicases are believed to be critical players in DNA damage, in addition to the main replicative helicase that we know about. Evolution over thousands of years can be trusted on why a single helicase is not enough. You may choose to focus on either experimental microscopy or on quantitative data analysis