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To be able to resolve molecular-clusters it is crucial to access vitalinformations (such as, molecule density and cluster-size) that are key tounderstand disease progression and the underlying mechanism. Traditionalsingle-molecule localization microscopy (SMLM) techniques use molecules ofvariable sizes (as determined by its localization precisions (LPs)) toreconstruct super-resolution map. This results in an image with overlapping andsuperimposing PSFs (due to a wide size-spectrum of single molecules) thatdegrade image resolution. Ideally it should be possible to identify thebrightest molecules (also termed as, fortunate molecules) to reconstructultra-superresolution map, provided sufficient statistics is available from therecorded data. POSSIBLE microscopy explores this possibility by introducingnarrow probability size-distribution of single molecules (narrow size-spectrumabout a predefined mean-size). The reconstruction begins by presetting the meanand variance of the narrow distribution function (Gaussian function).Subsequently, the dataset is processed and single molecule filtering is carriedout by the Gaussian distribution function to filter out unfortunate molecules.The fortunate molecules thus retained are then mapped to reconstructultra-superresolution map. In-principle, the POSSIBLE microscopy technique iscapable of infinite resolution (resolution of the order of actual singlemolecule size) provided enough fortunate molecules are experimentally detected.In short, bright molecules (with large emissivity) holds the key. Here, wedemonstrate the POSSIBLE microscopy technique and reconstruct single moleculeimages with an average PSF sizes of 15 nm, 30 nm and 50 nm. Results showbetter-resolved Dendra2-HA clusters with large cluster-density in transfectedNIH3T3 fibroblast cells as compared to the traditional SMLM techniques.

Probabilistic Optically-Selective Single-molecule Imaging Based Localization Encoded (POSSIBLE) Microscopy for Ultra-superresolution Imaging