  To be able to resolve molecular-clusters it is crucial to access vital
informations (such as, molecule density and cluster-size) that are key to
understand disease progression and the underlying mechanism. Traditional
single-molecule localization microscopy (SMLM) techniques use molecules of
variable sizes (as determined by its localization precisions (LPs)) to
reconstruct super-resolution map. This results in an image with overlapping and
superimposing PSFs (due to a wide size-spectrum of single molecules) that
degrade image resolution. Ideally it should be possible to identify the
brightest molecules (also termed as, fortunate molecules) to reconstruct
ultra-superresolution map, provided sufficient statistics is available from the
recorded data. POSSIBLE microscopy explores this possibility by introducing
narrow probability size-distribution of single molecules (narrow size-spectrum
about a predefined mean-size). The reconstruction begins by presetting the mean
and variance of the narrow distribution function (Gaussian function).
Subsequently, the dataset is processed and single molecule filtering is carried
out by the Gaussian distribution function to filter out unfortunate molecules.
The fortunate molecules thus retained are then mapped to reconstruct
ultra-superresolution map. In-principle, the POSSIBLE microscopy technique is
capable of infinite resolution (resolution of the order of actual single
molecule size) provided enough fortunate molecules are experimentally detected.
In short, bright molecules (with large emissivity) holds the key. Here, we
demonstrate the POSSIBLE microscopy technique and reconstruct single molecule
images with an average PSF sizes of 15 nm, 30 nm and 50 nm. Results show
better-resolved Dendra2-HA clusters with large cluster-density in transfected
NIH3T3 fibroblast cells as compared to the traditional SMLM techniques.
