Information-enhanced fluorescence imaging based on smart labels

Promovendus/a: Franziska Luisa Bierbüße

Promotor(en): Prof. dr. Peter Dedecker

Biology is complex. While fluorescence microscopy already offers many insights into biological processes, some biological functions remain hidden and cannot currently be observed. Further improvements of microscopy techniques will increase the information gained about complex biological samples. Additional benefits can, for instance, be won in terms of image quality. Quantified studies of molecules of interest or the visualization of multiple biological structures simultaneously also improves the biological understanding. During my PhD, I addressed these needs and proposed four novel methodologies. They are based on smart labels - so-called reversibly switchable fluorescent proteins. These labels are sensitive to light irradiation and their properties can be controlled by such. First, I improved the image quality of the microscopy technique 'super-resolution optical fluctuation imaging', which can profit from these fluorescent proteins, in a computationally efficient manner. I then quantified molecules of interest, such as calcium, combining a measurement and data analysis concept that makes use of smart labels. Furthermore, I provided a simulation tool AniSim to mathematically model and study fluorescence anisotropy experiments and gave an outlook how this can advance studies of large molecules using smart labels. Lastly, a technique visualizing and distinguishing four different overlapping biological structures was introduced. To conclude, the proposed tools open up new opportunities and offer insights into the complex world of biology.