Description

The Advanced Fluorescence Microscopy course will teach basic and advanced principles of fluorescence microscopy with special emphasis in live imaging and state-of-the-art technologies. Basic principles will include basic Fluorescence Spectroscopy and Spectral Analysis and Unmixing, Microscope Architecture and Proper Adjustments, Sample Preparation and Choice of proper fluorophores, endogenous probes and biosensors. It will explain Wide-field versus Optical sectioning microscopy and Confocal Microscopy in depth. The course will take an in depth look into advanced microscopy modalities including super-resolution (SIM, STED, SoRa, STORM) and the latest innovations in confocal super-resolution. It will teach live imaging TIRF (total internal reflection) and TIRF use for single molecule studies. A great emphasis will be given to live imaging to study protein dynamics inside tissues, cells, and small organisms, such as actin dynamics.  The Live Imaging Modalities will also include Spinning Disk with SoRa super-resolution, lightsheet, dual camera systems, multiphoton, microfluidics and high-content imaging. Technologies such as Ratiometric Imaging (ex. Calcium, pH, NADH), Ablation (Including DNA ablation), Traction Force Microscopy, FCS (Fluorescence Correlation Spectroscopy), FRAP (Fluorescence Recovery After Photobleaching), FRET (Forster Resonance Energy Transfer) and FLIM (Fluorescence Lifetime Imaging) will also be covered in detail by experts in these fields. The course will also focus on proper image analysis and visualization according to current published microscopy guidelines. The main objective is to teach students how they can combine state-of-the-art technologies and advanced microscopy modalities to excel in their projects. At the end of this course students will be able to generate hypotheses that include state-of-the-art microscopy and, most importantly, they will be able to explain the microscopy and will be able to produce high quality microscopy data that follows the current microscopy guidelines for data quality and reproducibility.