New software tool speeds up selection of microscopy proteins for sharper cell images
Researchers have created free software that predicts which fluorescent proteins will work best for super-resolution microscopy, removing much of the trial-and-error from imaging experiments. The tool could help biotech companies and research labs cut costs and accelerate drug discovery by designing better imaging protocols faster.
Originaltitel: A Versatile Tool to Predict and Guide RESOLFT Images Based on Photoswitching, Labelling and Optical Properties
<p>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.</p>