Quantification of trans-synaptic protein alignment: A data analysis case for single-molecule localization microscopy

Abstract

Nanoscale distribution of proteins and their relative positioning within a defined subcellular region are key to their physiological functions. Thanks to the super-resolution imaging methods, especially single-molecule localization microscopy (SMLM), mapping the three-dimensional distribution of multiple proteins has been easier and more efficient than ever. Nevertheless, in spite of the many tools available for efficient localization detection and image rendering, it has been a challenge to quantitatively analyze the 3D distribution and relative positioning of proteins in these SMLM data. Here, using heterogeneously distributed synaptic proteins as examples, we describe in detail a series of analytical methods including detection of nanoscale density clusters, quantification of the trans-synaptic alignment between these protein densities, and automatic en face projection and averaging. These analyses were performed within customized Matlab routines and we make the full scripts available. The concepts behind these analytical methods and the scripts can be adapted for quantitative analysis of spatial organization of other macromolecular complexes.

Keywords: Localization microscopy; Nanocluster; Nanocolumns; Protein enrichment; Stochastic optical reconstruction microscopy (STORM); Three-dimensional.