A Versatile Tool to Predict and Guide RESOLFT Images Based on Photoswitching, Labelling and Optical Properties

Reversibly switchable fluorescent proteins (RSFPs) transition many times between dark and fluorescent states under minimal light doses. The photoswitching can happen at different speed, contrast and length, and it is often challenging for users to select the optimal imaging scheme to generate images with high contrast and spatial resolution. Here, we experimentally investigate the photophysical properties of different RSFPs under imaging conditions, together with an in silico exploration of their role in nanoscale image formation. We developed open-source software that uses measured parameters such as brightness, switching speed, photoswitching fatigue, labelling densities, noise and illumination type to generate the related RESOLFT (reversible saturable/switchable optical fluorescence transition) super-resolution image. This tool can be used to select optimal imaging schemes for known RSFPs and to guide the rational development of new proteins.