A tessellation-based colocalization analysis approach for single-molecule localization microscopy

Abstract

Multicolor single-molecule localization microscopy (λSMLM) is a powerful technique to reveal the relative nanoscale organization and potential colocalization between different molecular species. While several standard analysis methods exist for pixel-based images, λSMLM still lacks such a standard. Moreover, existing methods only work on 2D data and are usually sensitive to the relative molecular organization, a very important parameter to consider in quantitative SMLM. Here, we present an efficient, parameter-free colocalization analysis method for 2D and 3D λSMLM using tessellation analysis. We demonstrate that our method allows for the efficient computation of several popular colocalization estimators directly from molecular coordinates and illustrate its capability to analyze multicolor SMLM data in a robust and efficient manner.

Recent Advances and Prospects in the Research of Nascent Adhesions

“…For example, very little is known about the crosstalk between integrins of the same and different types, recently reported for early adhesions (Bharadwaj et al, 2017;Strohmeyer et al, 2017;Diaz et al, 2020;Samaržija et al, 2020). However, new research avenues in studying molecular interactions in NAs can emerge only from advances in the development of robust quantitative colocalization analysis (Levet et al, 2019). This needs to be accompanied by progress in genome editing and novel protein labeling strategies that could enable quantitative SR.…”

Nanoscale Distribution of Nuclear Sites by Super-Resolved Image Cross-Correlation Spectroscopy

“…In general, object-based analysis can be performed on any type of super-resolution image as long as the target objects are well-resolved and identified. In particular, object-based methods are often the methods of choice in SMLM, in which the acquired data are already segmented into a list of x , y coordinates of individual molecules ( 19 , 20 , 21 , 22 , 23 ). In principle, object-based analysis provides a full description of the spatial distribution of the two labeled species: in fact, knowledge of the object coordinates allows 1) mapping the locations of the specimen with a higher level of proximity and 2) performing a statistical analysis of the relative distance between the particles.…”

Quantitative mapping of membrane nanoenvironments through single-molecule imaging of solvatochromic probes

“…Voronoi tessellations have been implemented previously for both clustering and colocalization analysis of SMLM data. This turns a list of coordinates into a 2D set of tessellated polygons 9,10 , with the coordinates being at the centre of the polygons such that every position within one polygon is closer to that point than any other ( Supplementary Figure 3 ). We implemented Voronoi tessellation on our GP SMLM data while retaining the GP value for each tile.…”