Improving STED microscopy with SUPPOSe: enhancing resolution from a single-image

Abstract

Here we apply the gSUPPOSe algorithm on images acquired using Stimulated Emission Depletion (STED) microscopy with the aim of improving the resolution limit achieved. We processed images of the nuclear pore complex (NPC) from cell lines in which the Nup96 nucleoporin was endogenously labeled. This reference protein forms a ring whose diameter is ∽107 nm with 8 corners ∽42 nm apart from each other. The stereotypic arrangement of proteins in the NPC has been used as reference structures to characterize the performance of a variety of microscopy techniques. STED microscopy images resolve the ring arrangement but not the eightfold symmetry of the NPC. After applying the gSUPPOSe algorithm to the STED images, we were able to solve the octagonal structure of the NPC. After processing 562 single NPC, the average radius of the NPC was found to be R = 54.2 +- 2.9 nm, being consistent with the theoretical distances of this structure. To verify that the solutions obtained are compatible with a NPC-type geometry, we rotate the solutions to optimally fit an eightfold symmetric pattern and we count the number of corners that contain at least one localization. Fitting a probabilistic model to the histogram of the number of bright corners gives an effective labeling efficiency of 31%, which is in agreement with the values reported in for other cell lines and ligands used in Single Molecule Localization microscopy, showing that SUPPOSe can reliably retrieve sub-resolution, nanoscale objects from single acquisitions even in noisy conditions.