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Updated: Mar 19, 2026

Ground State Depletion Super-resolution Imaging in Mammalian Cells
Published on: November 5, 2017
Stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA) for quantitative
Rengasayee Veeraraghavan1, Robert G Gourdie1,2
1Center for Heart and Regenerative Medicine Research, Virginia Tech Carilion Research Institute, Roanoke, VA 24016 gourdier@vtc.vt.edu saiv@vt.edu.
Abstract:
The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200-300 nm of each other in the xy-plane and within 500-700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and <50 nm along the z-axis; 2) STORM-RLA provides a quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins.
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