In our recent work by Alan Szalai et al, we present a method to detect underlying molecular organization invisible to the eye in low-density single-molecule localization microscopy (SMLM) images.

SMLM is fantastic to obtain super-resolved fluorescence images. However, it is often the case that the density of localizations is too low to obtain a clear image. Instead, sparse distributions of single molecules positions are obtained. The reason for this could be an inefficient labeling or an intrinsically low abundance of the proteins of interest.

In this work, we present a new method based on statistics of first-neighbor distances that reveals molecular fibrillar molecular organizations even at densities where visual inspection is useless.

Szalai et al. “Analysis of sparse molecular distributions in fibrous arrangements based on the distance to the first neighbor in single molecule localization microscopy

Nanoscale 12 (2020) 9495–9506 pdf